Seminar

Monday, Jul 20th, 2020, 17:00*Franca Hoffmann* (California Institute of Technology)**To be announced**

only video broadcast

Tuesday, Aug 4th, 2020, 11:00*Marco Mondelli* (IST Austria)**Understanding Gradient Descent for Over-parameterized Deep Neural Networks**

only video broadcast

Tuesday, Oct 6th, 2020, 11:00

*Constantino Tsallis* (Centro Brasileiro de Pesquisas Fisicas, Brazil)

**Modern statistical mechanics – Approaching complexity in natural, artificial and social sciences**

Cancelled due to the Corona pandemic

MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Tuesday, Nov 3rd, 2020, 11:00

*Philipp Petersen* (Universität Wien)

**tba**

MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Please note also the lectures in theCancelled due to the Corona pandemic

MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Tuesday, Nov 3rd, 2020, 11:00

MPI MIS Leipzig, room E1 05 (Leibniz-Saal)

Math Machine Learning seminar organized by Guido Montúfar

Courses

**Winter term 2020/2021**

*Nihat Ay:***Kernel Methods in Learning Theory (Course)***Nihat Ay, Juan Pablo Vigneaux:***Recent Developments Towards a New Theory of Generalisation (Seminar)***Jürgen Jost:***Dynamics of Neural Systems (Course)**

Conferences and Workshops

September 10 - 11, 2020

**GAMM Workshop Computational and Mathematical Methods in Data Science**

Organisers: *Max von Renesse, André Uschmajew*

Videobroadcast, hosted by MPI MIS Leipzig

February 22 - 25, 2021

**Conference "Mathematics of Machine Learning"**

Organisers: *Benjamin Gess, Guido Montúfar, Nihat Ay*

Center for Interdisciplinary Research (ZiF), Bielefeld University

Initiators | Nihat Ay, Christiane Görgen, Guido Montúfar, André Uschmajew | |
---|---|---|

Aim |
Data, in its many forms and across various disciplines, is becoming an essential source for research in the 21st century.
In fact, data driven knowledge extraction nowadays constitutes one of the core paradigms for scientific discovery. Therefore,
the development of efficient techniques for the integration of large data sets is more necessary than ever. Mathematics
offers efficient methodologies from its various well-developed subfields for achieving this goal. Recognising the broad
scientific expertise at the Max Planck Institute for Mathematics in the Sciences within the scope of data science, our
initiative aims at bundling the corresponding efforts and activities in order to consolidate and advance research on
Mathematics of Data.
| |

Participating Groups |
Information Theory of Cognitive Systems - Nihat AyAlgebraic Statistics - Christiane GörgenQuantum Information and High-Energy Physics (Leipzig University) - Stefan HollandsGeometry and Complex Systems - Jürgen JostDeep Learning Theory - Guido MontúfarOpinion dynamics and cultural Conflict in European Spaces - Eckehard OlbrichPattern formation, energy landscapes, and scaling laws - Felix OttoStructure of Evolution - Matteo SmerlakBioinformatics (Leipzig University) - Peter F. StadlerNonlinear Algebra - Bernd SturmfelsTensors and Optimization - André Uschmajew | |

Links |
Mathematics and Computer Science at Leipzig University ScaDS.AI - Center for Scalable Data Analytics and Artificail Intelligence Leipzig/Dressen COMinDS - GAMM Activity Group Computational and Mathematical Methods in Data Science |