3 papers
stat.ML2023
Modify Training Directions in Function Space to Reduce Generalization Error
Yi Yu, Wenlian Lu, Boyu Chen
We propose theoretical analyses of a modified natural gradient descent method in the neural network function space based on the eigendecompositions of neural tangent kernel and Fis…
q-bio.BM2022
Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model
Yaqin Li, Lingli Li, Yongjin Xu +1
De novo molecular design has facilitated the exploration of large chemical space to accelerate drug discovery. Structure-based de novo method can overcome the data scarcity of acti…
cs.LG2022
Chemical transformer compression for accelerating both training and inference of molecular modeling
Yi Yu, Karl Borjesson
Transformer models have been developed in molecular science with excellent performance in applications including quantitative structure-activity relationship (QSAR) and virtual scr…