8 citations · 21 across the 5 of their papers we have counts for
5 papers
SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation
Liang He, Peiran Jin, Yaosen Min +7
Proteins, essential to biological systems, perform functions intricately linked to their three-dimensional structures. Understanding the relationship between protein structures and…
FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation
Kaiyuan Gao, Qizhi Pei, Gongbo Zhang +3
Molecular docking is a pivotal process in drug discovery. While traditional techniques rely on extensive sampling and simulation governed by physical principles, these methods are…
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…
FABind: Fast and Accurate Protein-Ligand Binding
Qizhi Pei, Kaiyuan Gao, Lijun Wu +7
Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements i…
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation
Jinglin Liu, Yi Ren, Xu Tan +4
Non-autoregressive translation (NAT) achieves faster inference speed but at the cost of worse accuracy compared with autoregressive translation (AT). Since AT and NAT can share mod…