Learning and Inference
Head:
Sayan Mukherjee
Phone:
+49 (0) 341 - 9959 - 50
Fax:
+49 (0) 341 - 9959 - 658
Address:
Inselstr. 22
04103 Leipzig
Publications Sayan Mukherjee
Journal Articles 
Youngsoo Baek ; Wilkins Aquino and Sayan Mukherjee:
Generalized Bayes approach to inverse problems with model misspecification
In: Inverse problems,
39 (2023) 10, 105011
Bibtex DOI: 10.1088/1361-6420/acf51cMichele Caprio and Sayan Mukherjee:
Ergodic theorems in dynamic imprecise probability kinematics
In: International journal of approximate reasoning,
152 (2023), p. 325-343
Bibtex DOI: 10.1016/j.ijar.2022.10.016 ARXIV: https://arxiv.org/abs/2003.06502Nicolas Fraiman ; Sayan Mukherjee and Gugan Thoppe:
The shadow knows : empirical distributions of minimum spanning acycles and persistence
diagrams of random complexes
In: Discrete analysis,
2023 (2023), 2
Bibtex ARXIV: https://arxiv.org/abs/2012.14122 LINK: https://discreteanalysisjournal.com/article/73323Alyssa Shi ; Samuel I. Berchuck ; Alessandro A. Jammal ; Geetika Singh ; Sydney Hunt ; Kimberly Roche ; Sayan Mukherjee and Felipe A. Medeiros:
Identifying risk factors for blindness from glaucoma at first presentation to a tertiary
clinic
In: American journal of ophthalmology,
250 (2023), p. 130-137
Bibtex DOI: 10.1016/j.ajo.2023.02.006Samuel I. Berchuck ; Mark Janko ; Felipe A. Medeiros ; William Pan and Sayan Mukherjee:
Bayesian non-parametric factor analysis for longitudinal spatial surfaces
In: Bayesian analysis,
17 (2022) 2, p. 435-464
Bibtex DOI: 10.1214/20-BA1253 ARXIV: https://arxiv.org/abs/1911.04337Johannes R. Björk ; Mauna R. Dasari ; Kim Roche ; Laura Grieneisen ; Trevor J. Gould ; Jean-Christophe Grenier ; Vania Yotova ; Neil Gottel ; David Jansen ; Laurence R. Gesquiere ; Jacob B. Gordon ; Niki H. Learn ; Tim L. Wango ; Raphael S. Mututua ; J. Kinyua Warutere ; Lon'ida Siodi ; Sayan Mukherjee ; Luis B. Barreiro ; Susan C. Alberts ; Jack A. Gilbert ; Jenny Tung ; Ran Blekhman and Elizabeth A. Archie:
Synchrony and idiosyncrasy in the gut microbiome of wild baboons
In: Nature ecology and evolution,
6 (2022) 7, p. 955-964
Bibtex DOI: 10.1038/s41559-022-01773-4 ARXIV: https://www.biorxiv.org/content/10.1101/2021.11.24.469913v2Michele Caprio ; Andrea Aveni and Sayan Mukherjee:
Concerning three classes of non-Diophantine arithmetics
In: Involve : a journal of mathematics,
15 (2022) 5, p. 763-774
Bibtex DOI: 10.2140/involve.2022.15.763 ARXIV: https://arxiv.org/abs/2102.04197Justin Curry ; Sayan Mukherjee and Katharine Turner:
How many directions determine a shape and other sufficiency results for two topological
transforms
In: Transactions of the American Mathematical Society / B,
9 (2022), p. 1006-1043
Bibtex DOI: 10.1090/btran/122 ARXIV: https://arxiv.org/abs/1805.09782Kevin McGoff ; Sayan Mukherjee and Andrew Nobel:
Gibbs posterior convergence and the thermodynamic formalism
In: The annals of applied probability,
32 (2022) 1, p. 461-496
Bibtex DOI: 10.1214/21-AAP1685 ARXIV: https://arxiv.org/abs/1901.08641Kimberly E. Roche and Sayan Mukherjee:
The accuracy of absolute differential abundance analysis from relative count data
In: PLoS computational biology,
18 (2022) 7, e1010284
Bibtex DOI: 10.1371/journal.pcbi.1010284 ARXIV: https://www.biorxiv.org/content/10.1101/2021.12.06.471397v2Justin D. Silverman ; Kimberly Roche ; Zachary C. Holmes ; Lawrence A. David and Sayan Mukherjee:
Bayesian multinomial logistic normal models through Marginally Latent Matrix-T processes
In: Journal of machine learning research,
23 (2022) 7, p. 1-42
Bibtex ARXIV: https://arxiv.org/abs/1903.11695 LINK: https://jmlr.org/papers/v23/19-882.html CODE: https://github.com/jsilve24/fido_paper_codeBrian St. Thomas ; Lizhen Lin ; Lek-Heng Lim and Sayan Mukherjee:
Learning subspaces of different dimensions
In: Journal of computational and graphical statistics,
31 (2022) 2, p. 337-350
Bibtex DOI: 10.1080/10618600.2021.2000420 ARXIV: https://arxiv.org/abs/1404.6841 CODE: https://github.com/sayanmuk/Mixture-of-SubspacesWai Shing Tang ; Gabriel Monteiro da Silva ; Henry Kirveslahti ; Erin Skeens ; Bibo Feng ; Timothy Sudijono ; Kevin K. Yang ; Sayan Mukherjee ; Brenda Rubenstein and Lorin Crawford:
A topological data analytic approach for discovering biophysical signatures in protein
dynamics
In: PLoS computational biology,
18 (2022) 5, e1010045
Bibtex DOI: 10.1371/journal.pcbi.1010045 ARXIV: https://www.biorxiv.org/content/10.1101/2021.07.28.454240v2Mikael Vejdemo-Johansson and Sayan Mukherjee:
Multiple hypothesis testing with persistent homology
In: Foundations of data science,
4 (2022) 4, p. 667-705
Bibtex DOI: 10.3934/fods.2022018 ARXIV: https://arxiv.org/abs/1812.06491Jordan Bryan ; Arpita Mandan ; Gauri Kamat ; W. Kirby Gottschalk ; Alexandra Badea ; Kendra J. Adams ; J. Will Thompson ; Carol A. Colton ; Sayan Mukherjee and Michael W. Lutz:
Likelihood ratio statistics for gene set enrichment in Alzheimer's disease pathways
In: Alzheimer's and dementia,
17 (2021) 4, p. 561-573
Bibtex DOI: 10.1002/alz.12223 CODE: https://github.com/j-g-bTingran Gao ; Jacek Brodzki and Sayan Mukherjee:
The geometry of synchronization problems and learning group actions
In: Discrete and computational geometry,
65 (2021) 1, p. 150-211
Bibtex DOI: 10.1007/s00454-019-00100-2 ARXIV: https://arxiv.org/abs/1610.09051 CODE: https://github.com/trgao10/GOS-SynCutRachel A. Johnston ; Philippe Vullioud ; Jack Thorley ; Henry Kirveslahti ; Leyao Shen ; Sayan Mukherjee ; Courtney M. Karner ; Tim Clutton-Brock and Jenny Tung:
Morphological and genomic shifts in mole-rat 'queens' increase fecundity but reduce
skeletal integrity
In: eLife,
10 (2021), e65760
Bibtex DOI: 10.7554/eLife.65760 ARXIV: https://www.biorxiv.org/content/10.1101/2020.07.31.231266v2Weiwei Li ; Jan Hannig and Sayan Mukherjee:
Subspace clustering through sub-clusters
In: Journal of machine learning research,
22 (2021), 53
Bibtex ARXIV: https://arxiv.org/abs/1811.06580 LINK: https://www.jmlr.org/papers/v22/18-780.htmlBruce Wang ; Timothy Sudijono ; Henry Kirveslahti ; Tingran Gao ; Doug M. Boyer ; Sayan Mukherjee and Lorin Crawford:
A statistical pipeline for identifying physical features that differentiate classes
of 3D shapes
In: The annals of applied statistics :,
15 (2021) 2, p. 638-661
Bibtex DOI: 10.1214/20-AOAS1430 ARXIV: https://www.biorxiv.org/content/10.1101/701391v3Lorin Crawford ; Anthea Monod ; Andrew X. Chen ; Sayan Mukherjee and Raúl Rabadán:
Predicting clinical outcomes in glioblastoma : an application of topological and functional
data analysis
In: Journal of the American Statistical Association,
115 (2020) 531, p. 1139-1150
Bibtex DOI: 10.1080/01621459.2019.1671198 ARXIV: https://arxiv.org/abs/1611.06818 CODE: https://github.com/lorinanthony/SECTJustin D. Silverman ; Kimberly Roche ; Sayan Mukherjee and Lawrence A. David:
Naught all zeros in sequence count data are the same
In: Computational and structural biotechnology journal,
18 (2020), p. 2789-2798
Bibtex DOI: 10.1016/j.csbj.2020.09.014 ARXIV: https://www.biorxiv.org/content/10.1101/477794v1Samuel I. Berchuck ; Sayan Mukherjee and Felipe A. Medeiros:
Estimating rates of progression and predicting future visual fields in glaucoma using
a deep variational autoencoder
In: Scientific reports,
9 (2019), 18113
Bibtex DOI: 10.1038/s41598-019-54653-6 ARXIV: https://www.biorxiv.org/content/10.1101/652487v1Merve Cakir ; Sayan Mukherjee and Kris C. Wood:
Label propagation defines signaling networks associated with recurrently mutated cancer
genes
In: Scientific reports,
9 (2019), 9401
Bibtex DOI: 10.1038/s41598-019-45603-3 ARXIV: https://www.biorxiv.org/content/10.1101/320770v1Tauras Vilgalys ; Jeffrey Rogers ; Clifford J. Jolly ; Sayan Mukherjee and Jenny Tung:
Evolution of DNA methylation in Papio baboons
In: Molecular biology and evolution,
36 (2019) 3, p. 527-540
Bibtex DOI: 10.1093/molbev/msy227 ARXIV: https://www.biorxiv.org/content/10.1101/400093v1Alex D. Washburne ; Justin D. Silverman ; James T. Morton ; Daniel Becker ; Daniel Crowley ; Sayan Mukherjee ; Lawrence A. David and Raina K. Plowright:
Phylofactorization : a graph partitioning algorithm to identify phylogenetic scales
of ecological data
In: Ecological monographs,
89 (2019) 2, e01353
Bibtex DOI: 10.1002/ecm.1353 ARXIV: https://www.biorxiv.org/content/10.1101/235341v1 CODE: https://github.com/reptalex/phylofactorFeilun Wu ; Allison J. Lopatkin ; Daniel A. Needs ; Charlotte T. Lee ; Sayan Mukherjee and Lingchong You:
A unifying framework for interpreting and predicting mutualistic systems
In: Nature communications,
10 (2019), 242
Bibtex DOI: 10.1038/s41467-018-08188-5Scott Barish ; Sarah Nuss ; Ilya Strunilin ; Suyang Bao ; Sayan Mukherjee ; Corbin D. Jones and Pelin C. Volkan:
Combinations of DIPs and Dprs control organization of olfactory receptor neuron terminals
in Drosophila
In: PloS genetics,
14 (2018) 8, e1007560
Bibtex DOI: 10.1371/journal.pgen.1007560 ARXIV: https://www.biorxiv.org/content/10.1101/316109v2Lorin Crawford ; Kris C. Wood ; Xiang Zhou and Sayan Mukherjee:
Bayesian approximate kernel regression with variable selection
In: Journal of the American Statistical Association,
113 (2018) 524, p. 1710-1721
Bibtex DOI: 10.1080/01621459.2017.1361830 ARXIV: https://arxiv.org/abs/1508.01217 CODE: https://github.com/lorinanthony/BAKRTingran Gao ; Gabriel S. Yapuncich ; Ingrid Daubechies ; Sayan Mukherjee and Doug M. Boyer:
Development and assessment of fully automated and globally transitive geometric morphometric
methods, with application to a biological comparative dataset with high interspecific
variation
In: The anatomical record : advances in integrative anatomy and evolutionary biology,
301 (2018) 4, p. 636-658
Bibtex DOI: 10.1002/ar.23700 ARXIV: https://www.biorxiv.org/content/10.1101/086280v1Justin D. Silverman ; Heather K. Durand ; Rachael J. Bloom ; Sayan Mukherjee and Lawrence A. David:
Dynamic linear models guide design and analysis of microbiota studies within artificial
human guts
In: Microbiome,
6 (2018), 202
Bibtex DOI: 10.1186/s40168-018-0584-3 ARXIV: https://www.biorxiv.org/content/10.1101/306597v1 CODE: https://github.com/LAD-LAB/MALLARD-Paper-CodeShiwen Zhao ; Barbara E. Engelhardt ; Sayan Mukherjee and David B. Dunson:
Fast moment estimation for generalized latent Dirichlet models
In: Journal of the American Statistical Association,
113 (2018) 524, p. 1528-1540
Bibtex DOI: 10.1080/01621459.2017.1341839 ARXIV: https://arxiv.org/abs/1603.05324 CODE: https://github.com/judyboon/MELDOmer Bobrowski ; Sayan Mukherjee and Jonathan E. Taylor:
Topological consistency via kernel estimation
In: Bernoulli,
23 (2017) 1, p. 288-328
Bibtex DOI: 10.3150/15-BEJ744 ARXIV: https://arxiv.org/abs/1407.5272Lorin Crawford ; Sayan Mukherjee ; Sayan Mukherjee and Xiang Zhou:
Detecting epistasis with the marginal epistasis test in genetic mapping studies of
quantitative traits
In: PloS genetics,
13 (2017) 7, e1006869
Bibtex DOI: 10.1371/journal.pgen.1006869 ARXIV: https://www.biorxiv.org/content/10.1101/066985v3 CODE: https://github.com/lorinanthony/MAPITGregory Darnell ; Stoyan Georgiew ; Sayan Mukherjee and Barbara E. Engelhardt:
Adaptive randomized dimension reduction on massive data
In: Journal of machine learning research,
18 (2017), 140
Bibtex ARXIV: https://arxiv.org/abs/1504.03183 LINK: https://jmlr.org/papers/v18/15-143.html CODE: https://github.com/gdarnell/arsvdSimón Lunagómez ; Sayan Mukherjee ; Robert L. Wolpert and Edoardo M. Airoldi:
Geometric representations of random hypergraphs
In: Journal of the American Statistical Association,
112 (2017) 517, p. 363-383
Bibtex DOI: 10.1080/01621459.2016.1141686 ARXIV: https://arxiv.org/abs/0912.3648Joshua Lynch ; Karen Tang ; Sambhawa Priya ; Joanna Sands ; Margaret Sands ; Evan Tang ; Sayan Mukherjee ; Dan Knights and Ran Blekhaman:
HOMINID : a framework for identifying associations between host genetic variation
and microbiome composition
In: GigaScience,
6 (2017) 12, gix107
Bibtex DOI: 10.1093/gigascience/gix107 ARXIV: https://www.biorxiv.org/content/10.1101/081323v2 CODE: https://github.com/blekhmanlab/hominidJustin D. Silverman ; Alex D. Washburne ; Sayan Mukherjee and Lawrence A. David:
A phylogenetic transform enhances analysis of compositional microbiota data
In: eLife,
6 (2017), e21887
Bibtex DOI: 10.7554/eLife.21887 ARXIV: https://www.biorxiv.org/content/10.1101/072413v1 LINK: http://bioconductor.org/packages/release/bioc/vignettes/philr/inst/doc/philr-intro.html CODE: https://github.com/jsilve24/philrKatherine R. Singleton ; Lorin Crawford ; Elisabeth Tsui ; Haley E. Manchester ; Ophelia Maertens ; Xiaojing Liu ; Maria Liberti ; Anniefer N. Magpusao ; Drew J. Adams ; Jason W. Locasale ; Karen Cichowski ; Sayan Mukherjee and Kris C. Wood:
Melanoma therapeutic strategies that select against resistance by exploiting MYC-driven
evolutionary convergence
In: Cell reports,
21 (2017) 10, p. 2796-2812
Bibtex DOI: 10.1016/j.celrep.2017.11.022Shiquan Sun ; Michelle Hood ; Laura Scott ; Qinke Peng ; Sayan Mukherjee ; Jenny Tung and Xiang Zhou:
Differential expression analysis for RNAseq using Poisson mixed models
In: Nucleic acids research,
45 (2017) 11, e106
Bibtex DOI: 10.1093/nar/gkx204 ARXIV: https://www.biorxiv.org/content/10.1101/073403v2Alex D. Washburne ; Justin D. Silverman ; Jonathan W. Leff ; Doninic J. Bennett ; John L. Darcy ; Sayan Mukherjee ; Noah Fierer and Lawrence A. David:
Phylogenetic factorization of compositional data yields lineage-level associations
in microbiome datasets
In: PeerJ,
5 (2017), e2969
Bibtex DOI: 10.7717/peerj.2969 ARXIV: https://www.biorxiv.org/content/10.1101/074112v2 CODE: https://github.com/reptalex/phylofactorKevin J. Galinsky ; Gaurav Bhatia ; Po-Ru Loh ; Stoyan Georgiew ; Sayan Mukherjee ; Nick J. Patterson and Alkes L. Price:
Fast principal-component analysis reveals convergent evolution of ADH1B in Europe
and East Asia
In: American journal of human genetics : AJHG,
93 (2016) 3, p. 456-472
Bibtex DOI: 10.1016/j.ajhg.2015.12.022 ARXIV: https://www.biorxiv.org/content/10.1101/018143v4 CODE: https://github.com/DReichLab/EIGSayan Mukherjee and John Steenbergen:
Random walks on simplicial complexes and harmonics
In: Random structures and algorithms,
49 (2016) 2, p. 379-405
Bibtex DOI: 10.1002/rsa.20645 ARXIV: https://arxiv.org/abs/1310.5099Noah Snyder-Mackler ; William H. Majoros ; Michael L. Yuan ; Amanda O. Shaver ; Jacob B. Gordon ; Gisela H. Kopp ; Stephen A. Schlebusch ; Jeffrey D. Wall ; Susan C. Alberts ; Sayan Mukherjee ; Xiang Zhou and Jenny Tung:
Efficient genome-wide sequencing and low-coverage pedigree analysis from noninvasively
collected samples
In: Genetics,
203 (2016) 2, p. 699-714
Bibtex DOI: 10.1534/genetics.116.187492 ARXIV: https://www.biorxiv.org/content/10.1101/029520v1 CODE: http://www.xzlab.org/software.htmlShiwen Zhao ; Chuan Gao ; Sayan Mukherjee and Barbara E. Engelhardt:
Bayesian group factor analysis with structured sparsity
In: Journal of machine learning research,
17 (2016), 196
Bibtex ARXIV: https://arxiv.org/abs/1411.2698 LINK: https://jmlr.org/papers/v17/14-472.html CODE: https://github.com/judyboon/BASSOmer Bobrowski and Sayan Mukherjee:
The topology of probability distributions on manifolds
In: Probability theory and related fields,
161 (2015) 3/4, p. 651-686
Bibtex DOI: 10.1007/s00440-014-0556-x ARXIV: https://arxiv.org/abs/1307.1123Doug M. Boyer ; Jesus Puente ; Justin T. Gladman ; Chris Glynn ; Sayan Mukherjee ; Gabriel S. Yapuncich and Ingrid Daubechies:
A new fully automated approach for aligning and comparing shapes
In: The anatomical record : advances in integrative anatomy and evolutionary biology,
298 (2015) 1, p. 249-276
Bibtex DOI: 10.1002/ar.23084 LINK: https://sayanmuk.github.io/Auto3DGM/ CODE: https://github.com/sayanmuk/Auto3DGMKevin McGoff ; Sayan Mukherjee ; Andrew Nobel and Natesh Pillai:
Consistency of maximum likelihood estimation for some dynamical systems
In: The annals of statistics,
43 (2015) 1, p. 1-29
Bibtex DOI: 10.1214/14-AOS1259 ARXIV: https://arxiv.org/abs/1306.5603Kevin McGoff ; Sayan Mukherjee and Natesh Pillai:
Statistical inference for dynamical systems : a review
In: Statistics surveys,
9 (2015), p. 209-252
Bibtex DOI: 10.1214/15-SS111 ARXIV: https://arxiv.org/abs/1204.6265Elizabeth Munch ; Katharine Turner ; Paul Bendich ; Sayan Mukherjee ; Jonathan C. Mattingly and John Harer:
Probabilistic Fréchet means for time varying persistence diagrams
In: Electronic journal of statistics,
9 (2015) 1, p. 1173-1204
Bibtex DOI: 10.1214/15-EJS1030 ARXIV: https://arxiv.org/abs/1307.6530Garvesh Raskutti and Sayan Mukherjee:
The information geometry of mirror descent
In: IEEE transactions on information theory,
61 (2015) 3, p. 1451-1457
Bibtex DOI: 10.1109/TIT.2015.2388583 ARXIV: https://arxiv.org/abs/1310.7780Laughlin Stewart ; Evan L. MacLean ; David Ivy ; Vanessa Woods ; Eliot Cohen ; Kerri Rodriguez ; Matthew McIntyre ; Sayan Mukherjee ; Josep Call ; Juliane Kaminski ; Miklósi Adáms ; Richard W. Wrangham and Brian Hare:
Citizen science as a new tool in dog cognition research
In: PLOS ONE,
10 (2015) 9, e0135176
Bibtex DOI: 10.1371/journal.pone.0135176Diana Fusco ; Timothy J. Barnum ; Andrew E. Bruno ; Joseph R. Luft ; Edward H. Snell ; Sayan Mukherjee and Patrick Charbonneau:
Statistical analysis of crystallization database links protein physico-chemical features
with crystallization mechanism
In: PLOS ONE,
9 (2014) 7, e101123
Bibtex DOI: 10.1371/journal.pone.0101123Botong Huang ; Nicholas W. D. Jarrett ; Shivnath Babu ; Sayan Mukherjee and Jun Yang:
Cumulon : cloud-based statistical analysis from users perspective
In: Bulletin of the Technical Committee on Data Engineering,
37 (2014) 3, p. 77-89
Bibtex LINK: http://sites.computer.org/debull/A14sept/p77.pdfAbhinav Kapur ; John A. Schneider ; Daniel Heard ; Sayan Mukherjee ; Phil Schumm ; Ganesh Oruganti and Edward O. Laumann:
A digital network approach to infer sex behavior in emerging HIV epidemics
In: PLOS ONE,
9 (2014) 7, e101416
Bibtex DOI: 10.1371/journal.pone.0101416John Steenbergen ; Caroline Klivans and Sayan Mukherjee:
A Cheeger-type inequality on simplicial complexes
In: Advances in applied mathematics,
56 (2014), p. 56-77
Bibtex DOI: 10.1016/j.aam.2014.01.002 ARXIV: https://arxiv.org/abs/1209.5091Katharine Turner ; Yuriy Mileyko ; Sayan Mukherjee and John Harer:
Fréchet means for distributions of persistence diagrams
In: Discrete and computational geometry,
52 (2014) 1, p. 44-70
Bibtex DOI: 10.1007/s00454-014-9604-7 ARXIV: https://arxiv.org/abs/1206.2790Katharine Turner ; Sayan Mukherjee and Doug M. Boyer:
Persistent homology transform for modeling shapes and surfaces
In: Information and inference,
3 (2014) 4, p. 310-344
Bibtex DOI: 10.1093/imaiai/iau011 ARXIV: https://arxiv.org/abs/1310.1030Matthew Weiser ; Sayan Mukherjee and Terrence S. Furey:
Novel distal eQTL analysis demonstrates effect of population genetic architecture
on detecting and interpreting associations
In: Genetics,
198 (2014) 3, p. 879-893
Bibtex DOI: 10.1534/genetics.114.167791 CODE: https://fureylab.web.unc.edu/software/netlift/Osceola Whitney ; Andreas R. Pfenning ; Jason T. Howard ; Charles A. Blatti ; Fang Liu ; James M. Ward ; Rui Wang ; Jean-Nicolas Audet ; Manolis Kellis ; Sayan Mukherjee ; Saurabh Sinha ; Alexander J. Hartemink ; Anne E. West and Erich D. Jarvis:
Core and region-enriched networks of behaviorally regulated genes and the singing
genome
In: Science,
346 (2014) 6215, 1256780
Bibtex DOI: 10.1126/science.1256780Qing Xiong ; Sayan Mukherjee and Terrence S. Furey:
GSAASeqSP : a toolset for gene set association analysis of RNA-seq data
In: Scientific reports,
4 (2014), 6347
Bibtex DOI: 10.1038/srep06347Brian D. Bennett ; Qing Xiong ; Sayan Mukherjee and Terrence S. Furey:
Correction [update acknowledgement]: 'A predictive framework for integrating disparate
genomic data types using sample-specific gene set enrichment analysis and multi-task
learning' [In: PLOS ONE, 7 (2012) 9 , e44635]
In: PLOS ONE,
8 (2013) 9, p. 1-1
Bibtex DOI: 10.1371/annotation/c04cea96-35f4-4578-a891-639e30fddd59Jordan M. Blum ; Leonor Ano ; Zhizhong Li ; David Van Mater ; Brian D. Bennett ; Mohit Sachdeva ; Irina Lagutina ; Minsi Zhang ; Jeffrey K. Mito ; Christoph Lepper ; Corinne M. Linardic ; Sayan Mukherjee ; Gerad C. Grosveld ; Chen-Ming Fan and David G. Kirsch:
Distinct and overlapping sarcoma subtypes initiated from muscle stem and progenitor
cells
In: Cell reports,
5 (2013) 4, p. 933-940
Bibtex DOI: 10.1016/j.celrep.2013.10.020Dina Hafez ; Ting Ni ; Sayan Mukherjee ; Jun Zhu and Uwe Ohler:
Genome-wide identification and predictive modeling of tissue-specific alternative
polyadenylation
In: Bioinformatics,
29 (2013) 13, p. i108-i116
Bibtex DOI: 10.1093/bioinformatics/btt233P. Richard Hahn ; Carlos M. Carvalho and Sayan Mukherjee:
Partial factor modeling : predictor-dependent shrinkage for linear regression
In: Journal of the American Statistical Association,
108 (2013) 503, p. 999-1008
Bibtex DOI: 10.1080/01621459.2013.779843 ARXIV: https://arxiv.org/abs/1011.3725 CODE: https://github.com/sayanmuk/Partial-factorMolly Megraw ; Sayan Mukherjee and Uwe Ohler:
Sustained-input switches for transcription factors and microRNAs are central building
blocks of eukaryotic gene circuits
In: Genome biology,
14 (2013), R85
Bibtex DOI: 10.1186/gb-2013-14-8-r85Bradford A. Perez ; A. Paiman Ghafoori ; Chang-Lung Lee ; Samuel M. Johnston ; Yifan Li ; Jacob G. Moroshek ; Yan Ma ; Sayan Mukherjee ; Yongbaek Kim ; Christian T. Badea and David G. Kirsch:
Assessing the radiation response of lung cancer with different gene mutations using
genetically engineered mice
In: Frontiers in oncology,
3 (2013), 72
Bibtex DOI: 10.3389/fonc.2013.00072Daniel E. Runcie and Sayan Mukherjee:
Dissecting high-dimensional phenotypes with Bayesian sparse factor analysis of genetic
covariance matrices
In: Genetics,
194 (2013) 3, p. 753-767
Bibtex DOI: 10.1534/genetics.113.151217 ARXIV: https://arxiv.org/abs/1211.3706 CODE: https://github.com/sayanmuk/Sparse-G-Matrix-EstimationLaura A. Simmons Kovacs ; Michael B. Mayhew ; David A. Orlando ; Yuanjie Jin ; Qingyun Li ; Chenchen Huang ; Steven I. Reed ; Sayan Mukherjee and Steven B. Haase:
Erratum: 'Cyclin-dependent kinases are regulators and effectors of oscillations driven
by a transcription factor network' [In: Molecular cell, 45 (2012) 5, p. 669-679]
In: Molecular cell,
49 (2013) 6, p. 1177-1179
Bibtex DOI: 10.1016/j.molcel.2013.03.007Patrizia Stifanelli ; Teresa M. Creanza ; Roberto Anglani ; Vania C. Liuzzi ; Sayan Mukherjee ; Francesco P. Schena and Nicola Ancona:
A comparative study of covariance selection models for the inference of gene regulatory
networks
In: Journal of biomedical informatics,
46 (2013) 5, p. 894-904
Bibtex DOI: 10.1016/j.jbi.2013.07.002Deborah R. Winter ; Lingyun Song ; Sayan Mukherjee ; Terrence S. Furey and Gregory E. Crawford:
DNase-seq predicts regions of rotational nucleosome stability across diverse human
cell types
In: Genome research,
23 (2013) 7, p. 1118-1129
Bibtex DOI: 10.1101/gr.150482.112 LINK: https://www.researchgate.net/publication/236665983Qiang Wu ; Feng Liang and Sayan Mukherjee:
Kernel sliced inverse regression : regularization and consistency
In: Abstract and applied analysis,
2013 (2013), 540725
Bibtex DOI: 10.1155/2013/540725 CODE: https://github.com/sayanmuk/Kernel-Sliced-Inverse-RegressionBrian D. Bennett ; Qing Xiong ; Sayan Mukherjee and Terrence S. Furey:
A predictive framework for integrating disparate genomic data types using sample-specific
gene set enrichment analysis and multi-task learning
In: PLOS ONE,
7 (2012) 9, e44635
Bibtex DOI: 10.1371/journal.pone.0044635Daniel E. Runcie ; David A. Garfield ; Courtney C. Babbitt ; Jennifer A. Wygoda ; Sayan Mukherjee and Gregory A. Wray:
Genetics of gene expression responses to temperature stress in a sea urchin gene network
In: Molecular ecology,
21 (2012) 18, p. 4547-4562
Bibtex DOI: 10.1111/j.1365-294X.2012.05717.xLaura A. Simmons Kovacs ; Michael B. Mayhew ; David A. Orlando ; Yuanjie Jin ; Qingyun Li ; Chenchen Huang ; Steven I. Reed ; Sayan Mukherjee and Steven B. Haase:
Cyclin-dependent kinases are regulators and effectors of oscillations driven by a
transcription factor network
In: Molecular cell,
45 (2012) 5, p. 669-679
Bibtex DOI: 10.1016/j.molcel.2011.12.033Jenny Tung ; Marie J. E. Charpentier ; Sayan Mukherjee ; Jeanne Altmann and Susan C. Alberts:
Genetic effects on mating success and partner choice in a social mammal
In: The American naturalist,
180 (2012) 1, p. 113-129
Bibtex DOI: 10.1086/665993 LINK: https://hal.inrae.fr/hal-02079632v1Qing Xiong ; Nicola Ancona ; Elizabeth R. Hauser ; Sayan Mukherjee and Terrence S. Furey:
Integrating genetic and gene expression evidence into genome-wide association analysis
of gene sets
In: Genome research,
22 (2012) 2, p. 386-397
Bibtex DOI: 10.1101/gr.124370.111 LINK: http://gsaa.unc.edu/Annarita D'Addabbo ; Orazio Palmieri ; Anna Latiano ; Vito Annese ; Sayan Mukherjee and Nicola Ancona:
RS-SNP : a random-set method for genome-wide association studies
In: BMC genomics,
12 (2011), 166
Bibtex DOI: 10.1186/1471-2164-12-166Annarita D'Addabbo ; Orazio Palmieri ; Rosalia Maglietta ; Anna Latiano ; Sayan Mukherjee ; Vito Annese and Nicola Ancona:
Discovering genetic variants in Crohn's disease by exploring genomic regions enriched
of weak association signals
In: Digestive and liver disease,
43 (2011) 8, p. 623-631
Bibtex DOI: 10.1016/j.dld.2011.02.010Justin Guinney ; Qiang Wu and Sayan Mukherjee:
Estimating variable structure and dependence in multitask learning via gradients
In: Machine learning,
83 (2011) 3, p. 265-287
Bibtex DOI: 10.1007/s10994-010-5217-4Yuriy Mileyko ; Sayan Mukherjee and John Harer:
Probability measures on the space of persistence diagrams
In: Inverse problems,
27 (2011) 12, 124007
Bibtex DOI: 10.1088/0266-5611/27/12/124007 LINK: https://www.researchgate.net/publication/228570998Sayan Mukherjee:
Book reviw: 'Inference and prediction in large dimensions' by Dennis Bosq and Delphine
Blanke, Wiley, 2007
In: Journal of the American Statistical Association,
106 (2011) 496, p. 1642-1643
Bibtex DOI: 10.1198/jasa.2011.br1112Stoyan Georgiew ; Alan P. Boyle ; Karthik Jayasurya ; Xuan Ding ; Sayan Mukherjee and Uwe Ohler:
Evidence-ranked motif identification
In: Genome biology,
11 (2010), R19
Bibtex DOI: 10.1186/gb-2010-11-2-r19 CODE: https://ohlerlab.mdc-berlin.de/software/cERMIT_82/Rosalia Maglietta ; Angela Distaso ; Ada Piepoli ; Orazio Palumbo ; Massimo Carella ; Annarita D'Addabbo ; Sayan Mukherjee and Nicola Ancona:
On the reproducibility of results of pathway analysis in genome-wide expression studies
of colorectal cancers
In: Journal of biomedical informatics,
43 (2010) 3, p. 397-406
Bibtex DOI: 10.1016/j.jbi.2009.09.005Sayan Mukherjee:
Book reviw: 'Computational intelligence and feature selection: rough and fuzzy approaches'
by Richard Jensen and Qiang Shen, Wiley, 2008
In: Journal of the American Statistical Association,
105 (2010) 489, p. 438-438
Bibtex DOI: 10.1198/jasa.2010.br1003Sayan Mukherjee ; Qiang Wu and Ding-Xuan Zhou:
Learning gradients on manifolds
In: Bernoulli,
16 (2010) 1, p. 181-207
Bibtex DOI: 10.3150/09-BEJ206 ARXIV: https://arxiv.org/abs/1002.4283Qiang Wu ; Justin Guinney ; Mauro Maggioni and Sayan Mukherjee:
Learning gradients : predictive models that infer geometry and dependence
In: Journal of machine learning research,
11 (2010), p. 2175-2198
Bibtex LINK: https://jmlr.org/papers/v11/wu10a.htmlQiang Wu ; Feng Liang and Sayan Mukherjee:
Localized sliced inverse regression
In: Journal of computational and graphical statistics,
19 (2010) 4, p. 843-860
Bibtex DOI: 10.1198/jcgs.2010.08080 LINK: https://www.researchgate.net/publication/221619562 CODE: https://github.com/sayanmuk/Local-Sliced-Inverse-RegressionLuca Abatangelo ; Rosalia Maglietta ; Angela Distaso ; Annarita D'Addabbo ; Teresa Maria Creanza ; Sayan Mukherjee and Nicola Ancona:
Comparative study of gene set enrichment methods
In: BMC bioinformatics,
10 (2009), 275
Bibtex DOI: 10.1186/1471-2105-10-275David S. Hsu ; Chaitanya R. Acharya ; Bala S. Balakumaran ; Richard F. Riedel ; Mickey K. Kim ; Marvaretta Stevenson ; Sascha Tuchman ; Sayan Mukherjee ; William Barry ; Holly K. Dressman ; Joseph R. Nevins ; Scott Powers ; David Mu and Anil Potti:
Characterizing the developmental pathways TTF-1, NKX2-8, and PAX9 in lung cancer
In: Proceedings of the National Academy of Sciences of the United States of America,
106 (2009) 13, p. 5312-5317
Bibtex DOI: 10.1073/pnas.0900827106 LINK: https://www.researchgate.net/publication/24194234Jonathan Lesneck ; Sayan Mukherjee ; Zoya Yurkovetsky ; Merlise Clyde ; Jeffrey R. Marks ; Anna E. Lokshin and Joseph Y. Lo:
Do serum biomarkers really measure breast cancer?
In: BMC cancer,
9 (2009), 164
Bibtex DOI: 10.1186/1471-2407-9-164Jeffrey K. Mito ; Richard F. Riedel ; Leslie Dodd ; Guy Lahat ; Alexander J. Lazar ; Rebecca D. Dodd ; Lars Stangenberg ; William C. Eward ; Francis J. Hornicek ; Sam S. Yoon ; Brian E. Brigman ; Tyler Jacks ; Dina Lev ; Sayan Mukherjee and David G. Kirsch:
Cross species genomic analysis identifies a mouse model as undifferentiated Pleomorphic
Sarcoma/Malignant Fibrous Histiocytoma
In: PLOS ONE,
4 (2009) 11, e8075
Bibtex DOI: 10.1371/journal.pone.0008075Sayan Mukherjee:
Book reviw: 'The probabilistic method' by Noga Alon and Joel H. Spencer, Wiley, 3rd
ed., 2008
In: Journal of the American Statistical Association,
104 (2009) 488, p. 1723-1723
Bibtex DOI: 10.1198/jasa.2009.br0912Jenny Tung ; Olivier Fédrigo ; Ralph Haygood ; Sayan Mukherjee and Gregory A. Wray:
Genomic features that predict allelic imbalance in humans suggest patterns of constraint
on gene expression variation
In: Molecular biology and evolution,
26 (2009) 9, p. 2047-2059
Bibtex DOI: 10.1093/molbev/msp113Elena J. Edelman ; Justin Guinney ; Jen-Tsan Chi ; Phillip G. Febbo and Sayan Mukherjee:
Modeling cancer progression via pathway dependencies
In: PLoS computational biology,
4 (2008) 2, e28
Bibtex DOI: 10.1371/journal.pcbi.0040028Kelly H. Salter ; Chaitanya R. Acharya ; Kelli S. Walters ; Richard Redman ; Ariel Anguiano ; Katherine S. Garman ; Carey K. Anders ; Sayan Mukherjee ; Holly K. Dressman ; William T. Barry ; Kelly P. Marcom ; John Olson ; Joseph R. Nevins and Anil Potti:
An integrated approach to the prediction of chemotherapeutic response in patients
with breast cancer
In: PLOS ONE,
3 (2008) 4, e1908
Bibtex DOI: 10.1371/journal.pone.0001908Zhong Wang ; Huntington F. Willard ; Sayan Mukherjee and Terrence S. Furey:
Evidence of influence of genomic DNA sequence on human X chromosome inactivation
In: PLoS computational biology,
2 (2008) 9, e113
Bibtex DOI: 10.1371/journal.pcbi.0020113Jen-Tsan Chi ; Edwin H. Rodriguez ; Zhen Wang ; Dimitry S. A. Nuyten ; Sayan Mukherjee ; Matt Van de Rijn ; Marc J. Van de Vijver ; Trevor Hastie and Patrick O. Brown:
Gene expression programs of human smooth muscle cells : tissue-specific differentiation
and prognostic significance in breast cancers
In: PloS genetics,
9 (2007) 3, e164
Bibtex DOI: 10.1371/journal.pgen.0030164Elena Edelman ; Alessandro Porrello ; Justin Guinney ; Bala Balakumaran ; Andrea Bild ; Phillip G. Febbo and Sayan Mukherjee:
Analysis of sample set enrichment scores : assaying the enrichment of sets of genes
for individual samples in genome-wide expression profiles
In: Bioinformatics,
22 (2007) 14, p. e108-e116
Bibtex DOI: 10.1093/bioinformatics/btl231 LINK: http://www2.stat.duke.edu/~sayan/assess/index.shtmlLiang Goh ; Susan K. Murphy ; Sayan Mukherjee and Terrence S. Furey:
Genomic sweeping for hypermethylated genes
In: Bioinformatics,
23 (2007) 3, p. 281-288
Bibtex DOI: 10.1093/bioinformatics/btl620 LINK: https://www.researchgate.net/publication/6649900Feng Liang ; Sayan Mukherjee and Mike West:
The use of unlabeled data in predictive modeling
In: Statistical science,
22 (2007) 2, p. 189-205
Bibtex DOI: 10.1214/088342307000000032 ARXIV: https://arxiv.org/abs/0710.4618Natesh S. Pillai ; Qiang Wu ; Feng Liang ; Sayan Mukherjee and Robert L. Wolpert:
Characterizing the function space for Bayesian kernel models
In: Journal of machine learning research,
8 (2007), p. 1769-1797
Bibtex LINK: https://jmlr.csail.mit.edu/papers/v8/pillai07a.htmlSayan Mukherjee ; Partha Niyogi ; Tomaso Poggio and Ryan Rifkin:
Learning theory : stability is sufficient for generalization and necessary and sufficient
for consistency of empirical risk minimization
In: Advances in computational mathematics,
25 (2006) 1-3, p. 161-193
Bibtex DOI: 10.1007/s10444-004-7634-z LINK: https://www.researchgate.net/publication/220390884Sayan Mukherjee and Qiang Wu:
Estimation of gradients and coordinate covariation in classification
In: Journal of machine learning research,
7 (2006), p. 2481-2514
Bibtex LINK: https://jmlr.csail.mit.edu/papers/v7/mukherjee06b.htmlSayan Mukherjee and Ding-Xuan Zhou:
Learning coordinate covariances via gradients
In: Journal of machine learning research,
7 (2006), p. 519-549
Bibtex LINK: https://jmlr.csail.mit.edu/papers/v7/mukherjee06a.htmlDaniela Tropea ; Gabriel Kreiman ; Alvin Lyckman ; Sayan Mukherjee ; Hongbo Yu ; Sam Horng and Mriganka Sur:
Gene expression changes and molecular pathways mediating activity-dependent plasticity
in visual cortex
In: Nature neuroscience,
9 (2006) 5, p. 660-668
Bibtex DOI: 10.1038/nn1689 LINK: https://www.researchgate.net/publication/7148155Alexander Rahkhlin ; Dimitry Panchenko and Sayan Mukherjee:
Risk bounds for mixture density estimation
In: ESAIM : Probability and statistics,
9 (2005), p. 220-229
Bibtex DOI: 10.1051/ps:2005011Alexander Rakhlin ; Sayan Mukherjee and Tomaso Poggio:
Stability results in learning theory
In: Analysis and applications,
3 (2005) 4, p. 397-417
Bibtex DOI: 10.1142/S0219530505000650Aravind Subramanian ; Pablo Tomayo ; Vamsi K. Mootha ; Sayan Mukherjee ; Benjamin L. Ebert ; Michael A. Gillette ; Amanda Paulovich ; Scott L. Pomeroy ; Tood R. Golub ; Eric S. Lander and Jill P. Mesirov:
Gene set enrichment analysis : a knowledge-based approach for interpreting genome-wide
expression profiles
In: Proceedings of the National Academy of Sciences of the United States of America,
102 (2005) 43, p. 15545-15550
Bibtex DOI: 10.1073/pnas.0506580102 CODE: https://www.gsea-msigdb.org/gsea/index.jspAlejandro Sweet-Cordero ; Sayan Mukherjee ; Aravind Subramanian ; Han You ; Jeffrey J. Roix ; Christine Ladd-Acosta ; Jill Mesirov ; Todd R. Golub and Tyler Jacks:
An oncogenic KRAS2 expression signature identified by cross-species gene-expression
analysis
In: Nature genetics,
37 (2005) 1, p. 48-55
Bibtex DOI: 10.1038/ng1490 LINK: https://www.researchgate.net/publication/8120756Raanan Berger ; Phillip G. Febbo ; Pradip K. Majumder ; Jean J. Zhao ; Sayan Mukherjee ; Sabina Signoretti ; K. Thirza Campbell ; William R. Sellers ; Thomas M. Roberts ; Massimo Loda ; Todd R. Golub and William C. Hahn:
Androgen-induced differentiation and tumorigenicity of human prostate epithelial cells
In: Cancer research,
64 (2004) 24, p. 8867-8875
Bibtex DOI: 10.1158/0008-5472.CAN-04-2938Sayan Mukherjee ; Pablo Tamayo ; Simon Rogers ; Ryan Rifkin ; Anna Engle ; Colin Campbell ; Todd R. Golub and Jill P. Mesirov:
Estimating dataset size requirements for classifying DNA microarray data
In: Journal of computational biology,
10 (2004) 2, p. 119-142
Bibtex DOI: 10.1089/106652703321825928 LINK: https://www.researchgate.net/publication/10710727Tomaso Poggio ; Ryan Rifkin ; Sayan Mukherjee and Partha Niyogi:
General conditions for predictivity in learning theory
In: Nature,
428 (2004), p. 419-422
Bibtex DOI: 10.1038/nature02341Ryan Rinfkin ; Sayan Mukherjee ; Pablo Tamayo ; Sridhar Ramaswamy ; Chen-Hsiang Yeang ; Michael Angelo ; Michael Reich ; Tomaso Poggio ; Eric S. Lander ; Todd R. Golub and Jill P. Mesirov:
An analytical method for multiclass molecular cancer classification
In: SIAM review,
45 (2003) 4, p. 706-723
Bibtex DOI: 10.1137/S0036144502411986 LINK: https://www.researchgate.net/publication/228586586Olivier Chapelle ; Vladimir. Vapnik ; Olivier Bousquet and Sayan Mukherjee:
Choosing multiple parameters for support vector machines
In: Machine learning,
46 (2002) 1-3, p. 131-159
Bibtex DOI: 10.1023/A:1012450327387 LINK: https://www.researchgate.net/publication/2374270Lance D. Miller ; Philip M. Long ; Limsson Wong ; Sayan Mukherjee ; Lisa M. McShane and Edison T. Liu:
Optimal gene expression analysis by microarrays
In: Cancer cell,
2 (2002) 5, p. 353-361
Bibtex DOI: 10.1016/S1535-6108(02)00181-2Scott Pomeroy ; Pablo Tamayo ; Michelle Gaasenbeek ; Lisa M. Sturla ; Michael Angelo ; Margaret E. McLaughlin ; John Y. H. Kim ; Liliana C. Goumnerova ; Peter M. Black ; Ching Lau ; Jeffrey Allen ; David Zagzag ; James M. Olson ; Tom Curran ; Dynthia Wetmore ; Jaclyn A. Biegel ; Tomaso Poggio ; Sayan Mukherjee ; Ryan Rifkin ; Andrea Califano ; Gustavo Stolovitzky ; David N. Louis ; Jill P. Mesirov ; Eric S. Lander and Tood R. Golub:
Prediction of central nervous system embryonal tumour outcome based on gene expression
In: Nature,
415 (2002) 6870, p. 436-442
Bibtex DOI: 10.1038/415436a LINK: https://www.researchgate.net/publication/11550810Sridhar Ramaswamy ; Pablo Tomayo ; Ryan Rifkin ; Sayan Mukherjee ; Chen-Hsiang Yeang ; Michael Angelo ; Christine Ladd ; Michael Reich ; Eva Latulippe ; Jill P. Mesirov ; Tomaso Poggio ; William Gerald ; Massimo Loda ; Eric S. Lander and Todd R. Golub:
Multiclass cancer diagnosis using tumor gene expression signatures
In: Proceedings of the National Academy of Sciences of the United States of America,
98 (2001) 26, p. 15149-15154
Bibtex DOI: 10.1073/pnas.211566398Chen-Hsiang Yeang ; Sridhar Ramaswamy ; Pablo Tamayo ; Sayan Mukherjee ; Ryan Rifkin ; Michael Angelo ; Michael Reich ; Eric Lander ; Jill Mesirov and Todd Golub:
Molecular classification of multiple tumor types
In: Bioinformatics,
17 (2001) Suppl. 1, p. S316-S322
Bibtex DOI: 10.1093/bioinformatics/17.suppl_1.S316 LINK: https://www.researchgate.net/publication/31409732Publications in Books and Conference Proceedings
Xiangyu Zhang ; Ramin Bashizade ; Yicheng Wang ; Sayan Mukherjee and Alvin R. Lebeck:
Statistical robustness of Markov chain Monte Carlo accelerators
In: ASPLOS 2021 : Proceedings of the 26th ACM international conference on architectural
support for programming languages and operating systems ; virtual ; April 19 - 23,
2021 / Tim Sherwood (ed.)
Bibtex DOI: 10.1145/3445814.3446697 LINK: https://users.cs.duke.edu/~alvy/papers/robustness_asplos21.pdfNew York, NY : Association for Computing Machinery, 2021. - P. 959-974
Zilong Tan ; Kimberly Roche ; Xiang Zhou and Sayan Mukherjee:
Scalable algorithms for learning high-dimensional linear mixed model
In: Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence,
{UAI} 2018, Monterey, California, USA, August 6-10, 2018 / Amir Globerson... (eds.)
Bibtex ARXIV: https://arxiv.org/abs/1803.04431 LINK: http://auai.org/uai2018/proceedings/papers/99.pdf CODE: https://github.com/ztanml/arLMMCorvallis, Or. : AUAI Press, 2018. - P. 259-268
Zilong Tan and Sayan Mukherjee:
Partitioned tensor factorizations for learning mixed membership models
In: Proceedings of the 34th international conference on machine learning : 6-11 August
2017, International Convention Centre, Sydney, Australia / Doina Precup... (eds.)
Long Beach, California : PMLR, 2017. - P. 3358-3367
(Proceedings of machine learning research ; 70)
Bibtex ARXIV: https://arxiv.org/abs/1702.07933 LINK: http://proceedings.mlr.press/v70/tan17a.html CODE: https://github.com/ztanml/ptpqpSimón Lunagómez ; Sayan Mukherjee and Robert L. Wolpert:
Priors on hypergraphical models via simplicial complexes
In: Current trends in Bayesian methodology with applications / Satyanshu Upadhyay... (eds.)
Bibtex LINK: https://www.taylorfrancis.com/chapters/edit/10.1201/b18502-26/priors-hypergraphical-models-via-simplicial-complexesBoca Raton, FL : CRC Press, 2015. - P. 391-413
Garvesh Raskutti and Sayan Mukherjee:
The information geometry of mirror descent
In: Geometric science of information : second international conference, GSI 2015, Palaiseau,
France, October 28-30, 2015, proceedings / Frank Nielsen... (eds.)
Cham : Springer, 2015. - P. 359-368
(Lecture notes in computer science ; 9389)
Bibtex DOI: 10.1007/978-3-319-25040-3_39 ARXIV: https://arxiv.org/abs/1310.7780Wuzhou Zhang ; Pankaj K. Agarwal and Sayan Mukherjee:
Contour trees of uncertain terrains
In: SIGSPATIAL '15 : Proceedings of the 23rd SIGSPATIAL international conference on advances
in geographic information systems ; November 3 - 6, 2015 ; Washington, Seattle / Mohamed Ali... (eds.)
Bibtex DOI: 10.1145/2820783.2820823New York, NY : ACM, 2015
Paul Bendich ; Bei Wang and Sayan Mukherjee:
Local homology transfer and stratification learning
In: Proceedings of the 23rd annual ACM-SIAM symposium on discrete algorithms, SODA 2012,
Kyoto, Japan, January 17-19, 2012
Bibtex DOI: 10.1137/1.9781611973099.107Philadelphia, PA : Society for Industrial and Applied Mathematics, 2012. - P. 1355-1370
Elena Edelman ; Katherine Garman ; Anil Potti and Sayan Mukherjee:
Making mountains out of molehills : moving from single gene to pathway based models
of colon cancer progression
In: Medical biostatistics for complex diseases / Frank Emmert-Streib... (eds.)
Bibtex DOI: 10.1002/9783527630332.ch4Weinheim : Wiley-VCH, 2010. - P. 75-87
Justin Guinney ; Philip Febbo ; Mauro Maggioni and Sayan Mukherjee:
Multiscale factor models for molecular networks
In: JSM proceedings of the American Statistical Association : papers presented at the
joint statistical meetings 2010
Bibtex LINK: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.5746Alexandria, Va. : ASA, 2010. - P. 4887-4901
Kai Mao ; Feng Liang and Sayan Mukherjee:
Supervised dimension reduction using Bayesian mixture modeling
In: Proceedings of the thirteenth international conference on artificial intelligence
and statistics
Long Beach, California : PMLR, 2010. - P. 501-508
(Proceedings of machine learning research ; 9)
Bibtex LINK: https://proceedings.mlr.press/v9/mao10a.html CODE: https://github.com/sayanmuk/Bayesian-Mixture-of-InversesQiang Wu ; Sayan Mukherjee and Feng Liang:
Localized sliced inverse regression
In: Advances in neural information processing systems 21 : NIPS 2008
Bibtex LINK: https://proceedings.neurips.cc/paper/2008/hash/e3796ae838835da0b6f6ea37bcf8bcb7-Abstract.html CODE: https://github.com/sayanmuk/Local-Sliced-Inverse-RegressionLa Jolla, CA : Neural Information Processing Systems, 2008. - P. 1785-1792
Polina Golland ; Feng Liang ; Sayan Mukherjee and Dimitry Panchenko:
Permutation tests for classification
In: Learning theory.: 18th annual conference on learning theory, COLT 2005, Bertinoro,
Italy, June 27-30, 2005 ; proceedings / Peter Auer... (eds.)
Berlin : Springer, 2005. - P. 501-515
(Lecture notes in computer science ; 3559)
Bibtex DOI: 10.1007/11503415_34 LINK: http://cbcl.mit.edu/publications/ai-publications/2003/AIM-2003-019.pdfSayan Mukherjee:
Classifying microarray data using support vector machines
In: A practical approach to microarray data analysis / Daniel P. Berrar... (eds.)
Bibtex DOI: 10.1007/0-306-47815-3_9New York, NY : Kluwer Academic, 2003. - P. 166-185
Sayan Mukherjee ; Ryan Rifkin and Poggio Tomaso:
Regression and classification with regularization
In: Nonlinear estimation and classification / David D. Denison... (eds.)
New York : Springer, 2003. - P. 111-128
(Lecture notes in statistics ; 171)
Bibtex DOI: 10.1007/978-0-387-21579-2_7 LINK: https://www.researchgate.net/publication/2856752Tomaso Poggio ; Sayan Mukherjee ; Ryan Rifkin ; Alexander Rakhlin and Alessandro Verri:
B
In: Uncertainty in geometric computations / Joab Winkler... (eds.)
New York : Springer, 2002. - P. 131-141
(The Springer international series in engineering and computer science ; 704)
Bibtex DOI: 10.1007/978-1-4615-0813-7_11Javid Sadr ; Sayan Mukherjee ; K. Thoresz and Pawan Sinha:
The fidelity of local ordinal encoding
In: Advances in neural information processing systems 14 : NIPS 2001 ; proceedings of
the 2001 neural information processing systems conference / Thomas G. Dietterich... (eds.)
Bibtex LINK: https://papers.nips.cc/paper/2001/hash/84ddfb34126fc3a48ee38d7044e87276-Abstract.htmlCambridge, Mass. : MIT Press, 2002. - P. 1279-1286
Bernd Heisele ; Thomas Serre ; Sayan Mukherjee and Tomaso Poggio:
Feature reduction and hierarchy of classifiers for fast object detection in video
images
In: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern
recognition : CVPR 2001 ; Dec. 8 2001 to Dec. 14 2001 ; Kauai, Hawaii ; Volume 2
Bibtex DOI: 10.1109/CVPR.2001.990919 LINK: https://www.researchgate.net/publication/3940805Piscataway, NJ : IEEE, 2001. - P. 18-24
Leonid Peshkin and Sayan Mukherjee:
Bounds on sample size for policy evaluation in Markov environments
In: Computational learning theory : 14th annual conference, COLT 2001, and 5th European
conference, EuroCOLT 2001, Amsterdam, Netherlands, July 16-19, 2001 ; proceedings / David Helmbold... (eds.)
Berlin : Springer, 2001. - P. 616-629
(Lecture notes in computer science ; 2111)
Bibtex DOI: 10.1007/3-540-44581-1_41 ARXIV: https://arxiv.org/abs/cs/0105027Jason Weston ; Sayan Mukherjee ; Olivier Chapelle ; Massimiliano Pontil ; Tomaso Poggio and Vladimir. Vapnik:
Feature selection for SVMs
In: Advances in neural information processing systems 13 : NIPS 2000 ; proceedings of
the 2000 neural information processing systems conference / Todd K. Leen... (eds.)
Bibtex LINK: https://papers.nips.cc/paper/2000/hash/8c3039bd5842dca3d944faab91447818-Abstract.htmlCambridge, Mass. : MIT Press, 2001. - P. 668-674
Massimiliano Pontil ; Sayan Mukherjee and Federico Girosi:
On the noise model of support vector machines regression
In: Algorithmic learning theory : 11th international conference, ALT 2000, Sydney, Australia,
December 11-13, 2000 ; proceedings / Hiroki Arimura... (eds.)
Berlin : Springer, 2000. - P. 316-324
(Lecture notes in computer science ; 1968)
Bibtex DOI: 10.1007/3-540-40992-0_24 LINK: https://www.researchgate.net/publication/2524195Vladimir. Vapnik and Sayan Mukherjee:
Support vector method for multivariate density estimation
In: Advances in neural information processing systems 12 : NIPS 1999 ; proceedings of
1999 neural information processing systems conference / Sara A. Solla... (eds.)
Bibtex LINK: https://papers.nips.cc/paper/1999/hash/207f88018f72237565570f8a9e5ca240-Abstract.htmlCambridge, Mass. : MIT Press, 2000. - P. 659-665
Preprints
Yun Wei ; Sayan Mukherjee and Xuan Long Nguyen:
Minimum \(\Phi\)-distance estimators for finite mixing measures
Repository Open AccessShreya Arya ; Justin Curry and Sayan Mukherjee:
A sheaf-theoretic construction of shape space
Repository Open AccessMichelle Pistner Nixon ; Jeffrey Letourneau ; Lawrence David ; Sayan Mukherjee and Justin D. Silverman:
A statistical analysis of compositional surveys
Repository Open AccessRamin Bashizade ; Xiangyu Zhang ; Sayan Mukherjee and Alvin R. Lebeck:
Accelerating markov random field inference with uncertainty quantification
Repository Open AccessMichele Caprio and Sayan Mukherjee:
Extended probabilities and their application to statistical inference
Repository Open AccessHenry Kirveslahti and Sayan Mukherjee:
Representing fields without correspondences : the lifted Euler characteristic transform
Repository Open AccessLangxuan Su and Sayan Mukherjee:
A large deviation approach to posterior consistency in dynamical systems
Repository Open AccessAnna K. Yanchenko ; Mohammadreza Soltani ; Robert J. Ravier ; Sayan Mukherjee and Vahid Tarokh:
A methodology for exploring deep convolutional features in relation to hand-crafted
features with an application to music audio modeling
Bibtex ARXIV: https://arxiv.org/abs/2111.01050 CODE: https://github.com/aky4wn/convolutions-for-music-audio
Repository Open AccessMichele Caprio and Sayan Mukherjee:
Finite mixture models : a bridge with stochastic geometry and Choquet theory
Repository Open AccessZiyang Ding and Sayan Mukherjee:
At the intersection of deep sequential model framework and state-space model framework
: study on option pricing
Repository Open AccessDidong Li and Sayan Mukherjee:
Random Lie brackets that induce torsion : a model for noisy vector fields
Repository Open AccessAnna K. Yanchenko and Sayan Mukherjee:
Stanza : a nonlinear state space model for probabilistic inference in non-stationary
time series
Repository Open AccessXiangyu Zhang ; Ramin Bashizade ; Yicheng Wang ; Cheng Lyu ; Sayan Mukherjee and Alvin R. Lebeck:
Beyond application end-point results : quantifying statistical robustness of MCMC
accelerators
Repository Open AccessSamuel I. Berchuck ; Felipe A. Medeiros and Sayan Mukherjee:
Scalable modeling of spatiotemporal data using the variational autoencoder : an application
in glaucoma
(The annals of applied statistics :)
Bibtex ARXIV: https://arxiv.org/abs/1908.09195Justin D. Silverman ; Rachael J. Bloom ; Sharon Jiang ; Heather K. Durand ; Sayan Mukherjee and Lawrence A. David:
Measuring and mitigating PCR bias in microbiome data
Repository Open AccessZilong Zou ; Sayan Mukherjee ; Harbir Antil and Wilkins Aquino:
Adaptive particle-based approximations of the Gibbs posterior for inverse problems
Repository Open AccessJustin D. Silverman ; Liat Shenhav ; Eran Halperin ; Sayan Mukherjee and Lawrence A. David:
Statistical considerations in the design and analysis of longitudinal microbiome studies
Repository Open AccessZilong Tan and Sayan Mukherjee:
Learning integral representations of Gaussian processes
Repository Open AccessAbbas Zaidi and Sayan Mukherjee:
Gaussian process mixtures for estimating heterogeneous treatment effects
Repository Open AccessAnna K. Yanchenko and Sayan Mukherjee:
Classical music composition using state space models
Bibtex ARXIV: https://arxiv.org/abs/1708.03822 CODE: https://aky4wn.github.io/Classical-Music-Composition-Using-State-Space-Models/
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Optimal approximating Markov chains for Bayesian inference
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Towards stratification learning through homology inference
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