中文The Eleventh International Conference on Learning Representations (ICLR 2023) just released its accepted paper list. BioGeometry and Mila team has 5 papers accepted by the conference. These papers cover areas such as protein design, protein-ligand docking, protein & molecular representation learning, and node classification on text-attributed graphs. Advanced techniques, including generative models, geometric pretraining, contrastive learning, and variational inference, are proposed or utilized. Congratulations to all our researchers and collaborators!
ProtSeed: Protein Sequence and Structure Co-Design with Equivariant Translation
Joint sequence-structure translation enables fast generative protein design.
ICLR 2023
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
End-to-end protein-ligand docking with SE(3)-equivariance.
ICLR 2023
GearNet: Protein Representation Learning by Geometric Structure Pretraining
Multiview contrastive pretraining yields rich protein structure representations.
ICLR 2023
SE(3)-DDM: Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching
SE(3)-invariant 3D structure pretraining improves downstream performance.
ICLR 2023
GLEM: Learning on Large-scale Text-attributed Graphs via Variational Inference
GNN and LM fused as one with scalability & SOTA results on OGB datasets.
ICLR 2023 Notable Top 5%