Hanchen Wang

According to our database, Hanchen Wang authored at least 21 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Towards Artificial Intelligence Research Assistant for Expert-Involved Learning.

Tianyu Liu, Simeng Han, Xiao Luo, Hanchen Wang, Pan Lu, Biqing Zhu, Yuge Wang, Keyi Li, Jiapeng Chen, Rihao Qu, Yufeng Liu, Xinyue Cui, Aviv Yaish, Yuhang Chen, Minsheng Hao, Chuhan Li, Kexing Li, Arman Cohan, Hua Xu, Mark Gerstein, James Zou, Hongyu Zhao

CoRR, May, 2025

Learning Multi-cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States.

Tianyu Liu, Edward De Brouwer, Tony Kuo, Nathaniel Diamant, Alsu Missarova, Hanchen Wang, Minsheng Hao, Héctor Corrada Bravo, Gabriele Scalia, Aviv Regev, Graham Heimberg

Proceedings of the Research in Computational Molecular Biology, 2025

Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design.

Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Aviv Regev, Hanchen Wang, Tommaso Biancalani

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled.

Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang

Trans. Mach. Learn. Res., 2024

3D Interaction Geometric Pre-training for Molecular Relational Learning.

Namkyeong Lee, Yunhak Oh, Heewoong Noh, Gyoung S. Na, Minkai Xu, Hanchen Wang, Tianfan Fu, Chanyoung Park

CoRR, 2024

2023

Scientific discovery in the age of artificial intelligence.

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik

Nat., 2023

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

An Empirical Study of Retrieval-Enhanced Graph Neural Networks.

Dingmin Wang, Shengchao Liu, Hanchen Wang, Bernardo Cuenca Grau, Linfeng Song, Jian Tang, Le Song, Qi Liu

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2022

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt J. Kusner, Joan Lasenby, Qi Liu

CoRR, 2022

Augmenting Message Passing by Retrieving Similar Graphs.

Dingmin Wang, Shengchao Liu, Hanchen Wang, Linfeng Song, Jian Tang, Song Le, Bernardo Cuenca Grau, Qi Liu

CoRR, 2022

Pre-training Molecular Graph Representation with 3D Geometry.

Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Matching Point Sets with Quantum Circuit Learning.

Mohammadreza Noormandipour, Hanchen Wang

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Neural random subspace.

Yun-Hao Cao, Jianxin Wu, Hanchen Wang, Joan Lasenby

Pattern Recognit., 2021

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia

Nat. Mach. Intell., 2021

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia

CoRR, 2021

A Parameterised Quantum Circuit Approach to Point Set Matching.

Mohammadreza Noormandipour, Hanchen Wang

CoRR, 2021

Iterative Teaching by Label Synthesis.

Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Unsupervised Point Cloud Pre-training via Occlusion Completion.

Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matt J. Kusner

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Pre-Training by Completing Point Clouds.

Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matthew J. Kusner

CoRR, 2020

2019

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision.

Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller

CoRR, 2019