activity
20212026
most citedAdvancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning

2 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing cs.LGShow all

7 papers · 1 filter

cs.LG2026

Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance

Shiyun Wa, Yifei Wang, Simone Sciabola +1

Molecular similarity plays a central role in ligand-based drug discovery, such as virtual screening, analog searching, and goal-directed molecular generation. However, traditional…

cs.LG2025

Cross-Modality Controlled Molecule Generation with Diffusion Language Model

Yunzhe Zhang, Yifei Wang, Khanh Vinh Nguyen +1

The increasing variety of molecular data creates a need for generative models that can flexibly incorporate heterogeneous constraints across modalities. However, existing SMILES-ba…

cs.LG2023★ 2 cited

Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning

Yifei Wang, Yunrui Li, Lin Liu +2

The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective…

cs.LG2023

Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation

Yifei Wang, Zhengyang Zhou, Liqin Wang +4

When using machine learning to aid decision-making, it is critical to ensure that an algorithmic decision is fair and does not discriminate against specific individuals/groups, par…

cs.LG2022★ 1 cited

Motif-based Graph Representation Learning with Application to Chemical Molecules

Yifei Wang, Shiyang Chen, Guobin Chen +3

This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowin…

cs.LG2022

Knowledgebra: An Algebraic Learning Framework for Knowledge Graph

Tong Yang, Yifei Wang, Long Sha +2

Knowledge graph (KG) representation learning aims to encode entities and relations into dense continuous vector spaces such that knowledge contained in a dataset could be consisten…

cs.LG2021★ 2 cited

Predicting the Stereoselectivity of Chemical Transformations by Machine Learning

Justin Li, Dakang Zhang, Yifei Wang +3

Stereoselective reactions (both chemical and enzymatic reactions) have been essential for origin of life, evolution, human biology and medicine. Since late 1960s, there have been n…