Papers
I would have written a shorter letter, but I did not have the time.
—Blaise Pascal
- Controlling Directions Orthogonal to a Classifier
Yilun Xu, Hao He, Tianxiao Shen, Tommi Jaakkola.
In ICLR 2022 (Spotlight).
[PDF],[Code] - Learning Representations that Support Robust Transfer of Predictors
Yilun Xu, Tommi Jaakkola.
In preprint.
[PDF],[Code] - Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville.
In ICML 2021 (Long talk).
[PDF],[Code] - Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon.
In ICLR 2021.
[PDF],[Code] - A Theory of Usable Information under Computational Constraints
Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon.
In ICLR 2020 (Oral).
[PDF],[Code] - 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 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 NeurIPS 2019.
[PDF],[Code] - Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
Peng Cao*, Yilun Xu*, Yuqing Kong, Yizhou Wang.
In ICLR 2019.
[PDF],[Code]