Papers
Set your course by the stars, not by the lights of every passing ship.
- Hamiltonian Score Matching and Generative Flows
Peter Holderrieth, Yilun Xu, Tommi Jaakkola.
In Neural Information Processing Systems (NeurIPS), 2024.
[PDF] - On Physics-Inspired Generative Models
Yilun Xu.
PhD Thesis 🎓, Massachusetts Institute of Technology.
[PDF] - DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
Yilun Xu, Gabriele Corso, Tommi Jaakkola, Arash Vahdat, Karsten Kreis.
In International Conference on Machine Learning (ICML), 2024.
[PDF] ,[Project Page]
- Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi Jaakkola.
In International Conference on Learning Representations (ICLR), 2024; Deep Inverse Workshop, Neural Information Processing Systems (NeurIPS), 2023 (Oral); Workshop on Diffusion Models, Neural Information Processing Systems (NeurIPS), 2023.
[PDF] ,[Code]
Star - Restart Sampling for Improving Generative Processes
Yilun Xu*, Mingyang Deng*, Xiang Cheng*, Yonglong Tian, Ziming Liu, Tommi Jaakkola.
In Neural Information Processing Systems (NeurIPS), 2023.
[PDF] ,[Code]
News Coverage: [MarkTechPost],
Star - PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi Jaakkola.
In International Conference on Machine Learning (ICML), 2023.
[PDF] ,[Code] ,[Slide]
News Coverage: [MIT News], [Quanta Magazine], [Jiangmen Venture (CN)]
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- GenPhys: From Physical Processes to Generative Models
Ziming Liu, Di Luo, Yilun Xu, Tommi Jaakkola, Max Tegmark.
In preprint, 2023
[PDF]
News Coverage: [MIT News], [Quanta Magazine], - Stable Target Field for Reduced Variance Score Estimation in Diffusion Models
Yilun Xu*, Shangyuan Tong*, Tommi Jaakkola.
In International Conference on Learning Representations (ICLR), 2023
[PDF] ,[Code] ,[Slide] ,[Poster]
News Coverage: [MarkTechPost],
Star - Poisson Flow Generative Models
Yilun Xu*, Ziming Liu*, Max Tegmark, Tommi Jaakkola.
In Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
[PDF] ,[Code] ,[Slide] ,[Poster]
News Coverage: [MIT News], [Quanta Magazine], [AssemblyAI Blog], [MarkTechPost], [Synced (CN)], [PaperWeekly (CN)], [QbitAI (CN)],
Star - Controlling Directions Orthogonal to a Classifier
Yilun Xu, Hao He, Tianxiao Shen, Tommi Jaakkola.
In International Conference on Learning Representations (ICLR), 2022. (Spotlight)
[PDF] ,[Code] ,[Slide] ,[Poster]
Star - A Survey on Generative Diffusion Model
Hanqun Cao, Cheng Tan, Zhangyang Gao, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li.
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
[PDF] ,[Code]
Star - Learning Representations that Support Robust Transfer of Predictors
Yilun Xu, Tommi Jaakkola.
In preprint, 2022
[PDF] ,[Code] - Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville.
In International Conference on Machine Learning (ICML), 2021. (Long talk)
[PDF] - Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon.
In International Conference on Learning Representations (ICLR), 2021
[PDF] ,[Code] ,[Slide] ,[Poster]
Star - A Theory of Usable Information under Computational Constraints
Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon.
In International Conference on Learning Representations (ICLR), 2020. (Oral)
[PDF] ,[Code] ,[Slide] ,[Video]
News Coverage: [Synced (CN)], - TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
Xinwei Sun*, Yilun Xu*, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang.
In European Conference on Computer Vision (ECCV), 2020. (Oral)
[PDF] ,[Code] - L_{DMI} : A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise
Yilun Xu*, Peng Cao*, Yuqing Kong, Yizhou Wang.
In Neural Information Processing Systems (NeurIPS), 2019
[PDF] ,[Code] ,[Slide]
News Coverage: [Synced (CN)], [PKU-CFCS News (CN)]
Star - Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
Peng Cao*, Yilun Xu*, Yuqing Kong, Yizhou Wang.
In International Conference on Learning Representations (ICLR), 2019
[PDF] ,[Code] ,[Slide]
News Coverage: [PKU-CFCS News (CN)]
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