Schedule

DATE


TIME


ACTIVITY

Mon, Jul 11


08:30–09:30

Registration & Opening Remarks

09:30–10:30

Keynote 1 (Nickel)

Representation Learning and Generative Modeling on Manifolds [abstract]

10:30–11:00

Coffee Break

11:00–12:30

Tutorial 1 (Guigui)

Introduction to Geometric Statistics with Geomstats I [abstract]

12:30–12:40

Conference Photo

12:40–14:00

Lunch

14:00–14:40

Talk 1 (Pozzetti)

Graph Embeddings in Symmetric Spaces [abstract]

14:40–15:00

Coffee Break

15:00–15:40

Talk 2 (de Haan)
Gauge Equivariant Mesh Convolutional Neural Networks [abstract]

15:40–16:00

Coffee Break

Tue, Jul 12

09:30–10:30

Keynote 2 (Pennec)

Geometric Statistics for Computational Anatomy [abstract]

10:30–11:00

Coffee Break

11:00–12:30

Tutorial 2 (Kochurov)

Hyperbolic Manifolds in Deep Learning I [abstract]

12:30–14:00

Lunch

14:00–14:40

Talk 3 (Ommer)

Deep Metric and Representation Learning [abstract]

14:40–15:00

Coffee Break

15:00–15:40

Talk 4 (Bekkers)

Geometric and Physical Quantities improve E(3) Equivariant Message Passing [abstract]

15:40–16:00

Coffee Break

17:30–20:00

Conference Dinner

Wed, Jul 13

09:30–10:30

Keynote 3 (Rodolà)

From Sound to Metric Priors: A New Paradigm for Shape Generation [abstract]

10:30–11:00

Coffee Break

11:00–11:40

Talk 5 (Kratsios)

Embedding Guarantees for Representations by Small Probabilistic Graph Transformers [abstract]

11:40–13:00

Lunch

13:00–14:30

Practical Tutorial 1 (Guigui)

Introduction to Geometric Statistics with Geomstats II [abstract]

14:30–15:00

Coffee Break

15:00–16:30

Practical Tutorial 2 (Kochurov)

Hyperbolic Manifolds in Deep Learning II [abstract]