Recordings of invited talks are now available — see program below.

This workshop aims to bring together researchers and practicioners from the emerging fields of Graph Representation Learning and Geometric Deep Learning. The workshop will feature invited talks and a poster session. There will be ample opportunity for discussion and networking.

ELLIS Workshop

This workshop is part of the ELLIS program on Geometric Deep Learning. For more information on the European Lab for Learning and Intelligent Systems (ELLIS) visit



Accepted Papers

* denotes equal contribution.


Recordings of invited talks are now available — see below.

Time Presenter
9.20-9.30 Opening remarks (Thomas Kipf)
9.30-10.00 Peter Battaglia: Learning Physics with Graph Neural Networks [video]
10.00-10.30 Natalia Neverova: Entity-level Video Understanding [video]
10.30-11.00 Break & networking (topic-specific breakout rooms)
11.00-11.30 Stephan Günnemann: Adversarial Robustness of Machine Learning Models for Graphs [video]
11.30-12.00 Yaron Lipman: Deep Learning of Irregular and Geometric Data [video]
12.00-12.15 Qi Liu: Hyperbolic Graph Neural Networks [video]
12.15-13.30 Lunch & networking (topic-specific breakout rooms)
13.30-14.00 Miltos Allamanis: Typilus: Neural Type Hints [video]
14.00-14.15 Noemi Montobbio: KerCNNs: Biologically Inspired Lateral Connections for Classification of Corrupted Images [video]
14.15-14.30 Pim de Haan: Natural Graph Convolutions [video]
14.30-15.00 Break & networking (topic-specific breakout rooms)
15.00-15.30 Poster spotlights (1min pre-recorded video per poster)
15.30-17.00 Poster session / networking in breakout rooms


This workshop is organized by: