69 citations · 201 across the 15 of their papers we have counts for
4 papers · 1 filter
Geometric Epitope and Paratope Prediction
Marco Pegoraro, Clémentine Dominé, Emanuele Rodolà +2
Antibody-antigen interactions play a crucial role in identifying and neutralizing harmful foreign molecules. In this paper, we investigate the optimal representation for predicting…
Evolving Computation Graphs
Andreea Deac, Jian Tang
Graph neural networks (GNNs) have demonstrated success in modeling relational data, especially for data that exhibits homophily: when a connection between nodes tends to imply that…
How does over-squashing affect the power of GNNs?
Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein +4
Graph Neural Networks (GNNs) are the state-of-the-art model for machine learning on graph-structured data. The most popular class of GNNs operate by exchanging information between…
Equivariant MuZero
Andreea Deac, Théophane Weber, George Papamakarios
Deep reinforcement learning repeatedly succeeds in closed, well-defined domains such as games (Chess, Go, StarCraft). The next frontier is real-world scenarios, where setups are nu…