 Distributional Counterfactual Explanations With Optimal TransportInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 |
 Max-Sliced Mutual InformationNeural Information Processing Systems (NeurIPS), 2023 |
 Recent Advances in Optimal Transport for Machine LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 |
 Learning Elastic Costs to Shape Monge DisplacementsNeural Information Processing Systems (NeurIPS), 2023 |
 Monge, Bregman and Occam: Interpretable Optimal Transport in
High-Dimensions with Feature-Sparse MapsInternational Conference on Machine Learning (ICML), 2023 |
 Markovian Sliced Wasserstein Distances: Beyond Independent ProjectionsNeural Information Processing Systems (NeurIPS), 2023 |
 Statistical, Robustness, and Computational Guarantees for Sliced
Wasserstein DistancesNeural Information Processing Systems (NeurIPS), 2022 |
 Spherical Sliced-WassersteinInternational Conference on Learning Representations (ICLR), 2022 |
 Riemannian Hamiltonian methods for min-max optimization on manifoldsSIAM Journal on Optimization (SIAM J. Optim.), 2022 |
 Revisiting Sliced Wasserstein on Images: From Vectorization to
ConvolutionNeural Information Processing Systems (NeurIPS), 2022 |
 Sinkhorn Distributionally Robust OptimizationOperational Research (OR), 2021 |
 Re-evaluating Word Mover's DistanceInternational Conference on Machine Learning (ICML), 2021 |
 Two-sample Test with Kernel Projected Wasserstein DistanceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
 Projection Robust Wasserstein BarycentersInternational Conference on Machine Learning (ICML), 2021 |
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