projects
MLIP Arena
A unified benchmark platform for evaluating machine learning interatomic potentials beyond conventional error metrics, focusing on physical soundness and practical utility.
Transformers Discover Molecular Structure Without Graph Priors
Demonstrating that standard Transformers can learn molecular properties directly from Cartesian coordinates, matching state-of-the-art equivariant GNNs without explicit graph structures or physical priors.