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 Extremal Domain Translation with Neural Optimal TransportNeural Information Processing Systems (NeurIPS), 2023 |
 Normalizing flow neural networks by JKO schemeNeural Information Processing Systems (NeurIPS), 2022 |
 Entropic Neural Optimal Transport via Diffusion ProcessesNeural Information Processing Systems (NeurIPS), 2022 |
 On amortizing convex conjugates for optimal transportInternational Conference on Learning Representations (ICLR), 2022 |
 Towards Explaining Distribution ShiftsInternational Conference on Machine Learning (ICML), 2022 Sean Kulinski David I. Inouye |
 Supervised Training of Conditional Monge MapsNeural Information Processing Systems (NeurIPS), 2022 |
 Meta Optimal TransportInternational Conference on Machine Learning (ICML), 2022 |
 Neural Optimal Transport with General Cost FunctionalsInternational Conference on Learning Representations (ICLR), 2022 |
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 Wasserstein Iterative Networks for Barycenter EstimationNeural Information Processing Systems (NeurIPS), 2022 |
 Neural Optimal TransportInternational Conference on Learning Representations (ICLR), 2022 |
 Variational Wasserstein gradient flowInternational Conference on Machine Learning (ICML), 2021 |
 Understanding Entropic Regularization in GANsInternational Symposium on Information Theory (ISIT), 2021 |
 Score-based Generative Neural Networks for Large-Scale Optimal TransportNeural Information Processing Systems (NeurIPS), 2021 |
 Riemannian Convex Potential MapsInternational Conference on Machine Learning (ICML), 2021 |
 Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2
BenchmarkNeural Information Processing Systems (NeurIPS), 2021 |
 Large-Scale Wasserstein Gradient FlowsNeural Information Processing Systems (NeurIPS), 2021 |
 Continuous Wasserstein-2 Barycenter Estimation without Minimax
OptimizationInternational Conference on Learning Representations (ICLR), 2021 |
 Continual Learning of Generative Models with Limited Data: From
Wasserstein-1 Barycenter to Adaptive CoalescenceIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 |
 Convex Potential Flows: Universal Probability Distributions with Optimal
Transport and Convex OptimizationInternational Conference on Learning Representations (ICLR), 2020 |
 Scalable Computations of Wasserstein Barycenter via Input Convex Neural
NetworksInternational Conference on Machine Learning (ICML), 2020 |
 Optimal transport mapping via input convex neural networksInternational Conference on Machine Learning (ICML), 2019 |
