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2020 – today
- 2024
[c10]Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang:
Binding-Adaptive Diffusion Models for Structure-Based Drug Design. AAAI 2024: 12671-12679- [c9]Zhilin Huang, Ling Yang, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang, Bin Cui, Wenming Yang:
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models. ICLR 2024 - [c8]Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu:
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization. ICLR 2024 - [c7]Zhilin Huang, Ling Yang, Xiangxin Zhou, Chujun Qin, Yijie Yu, Xiawu Zheng, Zikun Zhou, Wentao Zhang, Yu Wang, Wenming Yang:
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation. ICML 2024 - [c6]Xiangxin Zhou, Liang Wang, Yichi Zhou:
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process. ICML 2024 - [c5]Yijia Chen, Pinghua Chen, Xiangxin Zhou, Yingtie Lei, Ziyang Zhou, Mingxian Li:
Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model. IJCNN 2024: 1-8 - [i13]Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang:
Binding-Adaptive Diffusion Models for Structure-Based Drug Design. CoRR abs/2402.18583 (2024) - [i12]Xiangxin Zhou, Liang Wang, Yichi Zhou:
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process. CoRR abs/2403.04154 (2024) - [i11]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. CoRR abs/2403.07902 (2024) - [i10]Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu:
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization. CoRR abs/2403.13829 (2024) - [i9]Yi Xiao, Xiangxin Zhou, Qiang Liu, Liang Wang:
Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule. CoRR abs/2403.13830 (2024) - [i8]Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang, Quanquan Gu:
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization. CoRR abs/2403.16576 (2024) - [i7]Yijia Chen, Pinghua Chen, Xiangxin Zhou, Yingtie Lei, Ziyang Zhou, Mingxian Li:
Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model. CoRR abs/2404.07072 (2024) - [i6]Xiwei Cheng, Xiangxin Zhou, Yuwei Yang, Yu Bao, Quanquan Gu:
Decomposed Direct Preference Optimization for Structure-Based Drug Design. CoRR abs/2407.13981 (2024) - [i5]Fei Ye, Zaixiang Zheng, Dongyu Xue, Yuning Shen, Lihao Wang, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, Quanquan Gu:
ProteinBench: A Holistic Evaluation of Protein Foundation Models. CoRR abs/2409.06744 (2024) - 2023
- [j2]Yuchi Liu
, Zhongdao Wang, Xiangxin Zhou, Liang Zheng:
A Study of Using Synthetic Data for Effective Association Knowledge Learning. Mach. Intell. Res. 20(2): 194-206 (2023) - [c4]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. ICML 2023: 11827-11846 - [c3]Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu:
GSLB: The Graph Structure Learning Benchmark. NeurIPS 2023 - [i4]Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu:
GSLB: The Graph Structure Learning Benchmark. CoRR abs/2310.05174 (2023) - 2021
- [j1]Hongzhi Shi, Yong Li, Hancheng Cao, Xiangxin Zhou, Chao Zhang, Vassilis Kostakos:
Semantics-Aware Hidden Markov Model for Human Mobility. IEEE Trans. Knowl. Data Eng. 33(3): 1183-1194 (2021) - [i3]Yuchi Liu, Zhongdao Wang, Xiangxin Zhou, Liang Zheng:
Synthetic Data Are as Good as the Real for Association Knowledge Learning in Multi-object Tracking. CoRR abs/2106.16100 (2021)
2010 – 2019
- 2019
- [c2]Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu:
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks. NeurIPS 2019: 6379-6391 - [c1]Hongzhi Shi, Hancheng Cao, Xiangxin Zhou, Yong Li, Chao Zhang, Vassilis Kostakos, Funing Sun, Fanchao Meng:
Semantics-Aware Hidden Markov Model for Human Mobility. SDM 2019: 774-782 - [i2]Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, Gang Yu:
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection. CoRR abs/1908.09492 (2019) - [i1]Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Ji Liu, Jungong Han:
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks. CoRR abs/1909.12778 (2019)
Coauthor Index
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