Learning Counterfactually Invariant Predictors.
Trans. Mach. Learn. Res., 2024
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Iterative Teaching by Data Hallucination.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Spectral Representation Learning for Conditional Moment Models.
CoRR, 2022
Improving Generative Moment Matching Networks with Distribution Partition.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models.
Proceedings of the 8th International Conference on Learning Representations, 2020
DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures.
CoRR, 2019
A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels.
CoRR, 2019
Cluster Alignment With a Teacher for Unsupervised Domain Adaptation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Semi-crowdsourced Clustering with Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
ZhuSuan: A Library for Bayesian Deep Learning.
CoRR, 2017
Conditional Generative Moment-Matching Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016