34 citations · 111 across the 7 of their papers we have counts for
4 papers · 1 filter
From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
Yaosen Min, Ye Wei, Peizhuo Wang +10
Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity predi…
Quantized Training of Gradient Boosting Decision Trees
Yu Shi, Guolin Ke, Zhuoming Chen +2
Recent years have witnessed significant success in Gradient Boosting Decision Trees (GBDT) for a wide range of machine learning applications. Generally, a consensus about GBDT's tr…
An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets
Yu Shi, Shuxin Zheng, Guolin Ke +7
This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation. The "Graphormer-V…
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
Yu Shi, Shuxin Zheng, Guolin Ke +7
This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation. With these simple…