research
∙
03/11/2023
Enhancing Protein Language Models with Structure-based Encoder and Pre-training
Protein language models (PLMs) pre-trained on large-scale protein sequen...
share
research
∙
01/28/2023
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction
Pre-training methods on proteins are recently gaining interest, leveragi...
research
∙
09/30/2022
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree
Retrosynthetic planning plays a critical role in drug discovery and orga...
research
∙
05/16/2022
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Answering complex first-order logic (FOL) queries on knowledge graphs is...
research
∙
03/11/2022
Protein Representation Learning by Geometric Structure Pretraining
Learning effective protein representations is critical in a variety of t...
research
∙
02/22/2022
Structured Multi-task Learning for Molecular Property Prediction
Multi-task learning for molecular property prediction is becoming increa...
research
∙
02/16/2022
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
Machine learning has huge potential to revolutionize the field of drug d...
research
∙
06/13/2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Link prediction is a very fundamental task on graphs. Inspired by tradit...
research
∙
02/06/2021
