04103 Leipzig

Germany E1 05 (Leibniz-Saal)

# Workshop on Geometry and Machine Learning

Geometry plays a crucial role in many Machine Learning problems, as it effectively captures the underlying structure and regularity of data. Additionally, Geometry provides a versatile framework for analyzing, unifying and generalizing Machine Learning methods to new settings.

GaML-23 aims to foster interaction and collaboration among researchers and practitioners working at the intersection of Geometry and Machine Learning. The Workshop will consist of invited talks, including keynotes by well-known experts and hands-on tutorials on implementing Geometric Machine Learning algorithms.

**Speakers:**

**Plenary Speakers**

- Heather Harrington
- Stefanie Jegelka
- Sebastian Pokutta

**Invited Talks**

- Sophie Achard
- Erik Bekkers
- Marzieh Eidi
- Kathlén Kohn
- Anastasis Kratsios
- Guido Montúfar
- Sayan Mukherjee
- Jeff Phillips
- Emanuele Rodola
- Vahid Shahverdi
- Rishi Sonthalia
- Jan Stühmer
- Sascha Timme
- Francesca Tombari
- Angelica Torres

**Funding**

Limited funds are available to cover some travel and accommodation costs for early-career participants, mainly targeting postdoctoral researchers and Ph.D. students. Applicants are expected to submit a brief academic CV and a statement of purpose, Ph.D. students applying for funding must additionally provide a letter of support from advisor(s). The funding application is included in the registration form.

**Deadlines**

Applications for funding requests are closed now.

In-person registration for the Main Venue (MPI MiS, E1 05) has reached capacity and is now closed. It is still possible to register for the live stream.

**WARNING: Please be wary if a company directly contacts you regarding payment for accommodation in Leipzig: this is fraud / phishing.**