Automatic dataset shift identification to support safe deployment of medical imaging AIInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024 |
Convergence of flow-based generative models via proximal gradient
descent in Wasserstein spaceIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023 |
R-divergence for Estimating Model-oriented Distribution DiscrepancyNeural Information Processing Systems (NeurIPS), 2023 |
Kernel-Based Tests for Likelihood-Free Hypothesis TestingNeural Information Processing Systems (NeurIPS), 2023 |
Sequential Predictive Two-Sample and Independence TestingNeural Information Processing Systems (NeurIPS), 2023 |
AutoML Two-Sample TestNeural Information Processing Systems (NeurIPS), 2022 |
A Manifold Two-Sample Test Study: Integral Probability Metric with
Neural NetworksInformation and Inference A Journal of the IMA (JIII), 2022 |
A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn
Uncertainty SetsInternational Symposium on Information Theory (ISIT), 2022 Jie Wang Yao Xie |
Neural Tangent Kernel Maximum Mean DiscrepancyNeural Information Processing Systems (NeurIPS), 2021 Xiuyuan Cheng Yao Xie |
A Witness Two-Sample TestInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
Learning Kernel Tests Without Data SplittingNeural Information Processing Systems (NeurIPS), 2020 |
Learning Deep Kernels for Non-Parametric Two-Sample TestsInternational Conference on Machine Learning (ICML), 2020 |