Yuxuan Song「宋宇轩」

I am a Second-year Ph.D. student in the Institute for Artificial Industry Research at Tsinghua University, advised by Prof. Weiying Ma. Previously, I used to be a researcher at Bytedance AI Lab, where I worked on deep generative models as well as their application in structured data with Prof. Hao Zhou and Prof. Lei Li. Before that, I received my bachelor and master degree from Shanghai Jiao Tong University (SJTU) where I am fortunate to be advised by Prof. Yong Yu.

Email  /  CV  /  Google Scholar  /  Twitter  /  Github

profile photo
Research Fields

My current research focus on Deep Generative Models and AI4Science. I am particularly interested in developing effective and scalable machine learning algorithms to solve the challenging problems in science such as protein folding, molecule generation and material design etc.

Selected Publications(* equal contribution)

MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space [pdf][code]
Yanru Qu*, Keyue Qiu*, Yuxuan Song*, Jingjing Gong, Jiawei Han, Mingyue Zheng, Hao Zhou, Weiying Ma
International Conference on Machine Learning (ICML), 2024.

Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks [pdf][code]
Yuxuan Song*, Jingjing Gong*, Hao Zhou, Mingyue Zheng,Jingjing Liu, Weiying Ma
International Conference on Learning Representations (ICLR), 2024.
Oral Presentation [85/7262]

Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation [pdf][code]
Yuxuan Song*, Jingjing Gong*, Ziyao Cao, Minkai Xu, Stefano Ermon, Hao Zhou, Weiying Ma
Neural Information Processing Systems (NeurIPS), 2023.

Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D [pdf][code]
Bo Qiang*, Yuxuan Song*, Minkai Xu, Bowen Gao, Hao Zhou, Weiying Ma, Yanyan Lan
International Conference on Machine Learning (ICML), 2023.

Follow Your Path: a Progressive Method for Knowledge Distillation. [pdf]
Wenxian Shi*, Yuxuan Song*,Hao Zhou, Lei Li
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2021

Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation. [pdf]
Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li
Artificial Intelligence and Statistics (AISTATS) 2020.

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip. [pdf][code]
Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao, Yong Yu
AAAI Conference on Artificial Intelligence (AAAI), 2020.


I am a die-hard fan of Liaoning Flying Leopard. I adopted a lovely Ragdoll (many thanks to Changzhi Sun).

Updated at May. 2024
Thanks Jon Barron for this amazing work