191 citations · 371 across the 9 of their papers we have counts for
9 papers
RetroMPA: A Molecular Property-Aware Auxiliary Framework for Enhancing Retrosynthesis Prediction
Mianzhi Liu, Fan Xiao, Zhiliang Yu +5
Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they autonomously learn reaction pat…
SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation
Fanglei Xue, Meihan Zhang, Shuqi Li +5
Targeted protein degradation (TPD) induced by small molecules has emerged as a rapidly evolving modality in drug discovery, targeting proteins traditionally considered "undruggable…
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Guikun Chen, Xu Zhang, Xiaolin Hu +3
Chemical reaction data is a pivotal asset, driving advances in competitive fields such as pharmaceuticals, materials science, and industrial chemistry. Its proprietary nature rende…
Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data
Chao Liang, Linchao Zhu, Zongxin Yang +2
We focus on the challenging problem of learning an unbiased classifier from a large number of potentially relevant but noisily labeled web images given only a few clean labeled ima…
Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
Lei Zhang, Zhenwei He, Yi Yang +2
The traditional object retrieval task aims to learn a discriminative feature representation with intra-similarity and inter-dissimilarity, which supposes that the objects in an ima…
VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification
Zhedong Zheng, Tao Ruan, Yunchao Wei +2
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and discriminative visual representation, given the significant intra-class vehicle variations acr…