sinkhorn divergence

Synthesis and Analysis of Data as Probability Measures With Entropy-Regularized Optimal Transport AISTATS 2025 Distributional Reinforcement Learning with Regularized Wasserstein Loss NeurIPS 2024 Feature-aligned N-BEATS with Sinkhorn divergence ICLR 2024 Understanding Entropic Regularization in GANs JMLR 2024 An Homogeneous Unbalanced Regularized Optimal Transport Model with Applications to Optimal Transport with Boundary AISTATS 2023 Estimating Regression Predictive Distributions with Sample Networks AAAI 2023 The Monge Gap: A Regularizer to Learn All Transport Maps ICML 2023 Improving Neural Cross-Lingual Abstractive Summarization via Employing Optimal Transport Distance for Knowledge Distillation AAAI 2022 Direct Measure Matching for Crowd Counting IJCAI 2021 Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence NeurIPS 2021 Hilbert Sinkhorn Divergence for Optimal Transport CVPR 2021 Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning NeurIPS 2020 Faster Wasserstein Distance Estimation with the Sinkhorn Divergence NeurIPS 2020 Linear Time Sinkhorn Divergences using Positive Features NeurIPS 2020 Sinkhorn Barycenter via Functional Gradient Descent NeurIPS 2020 Sinkhorn Natural Gradient for Generative Models NeurIPS 2020 Synchronizing Probability Measures on Rotations via Optimal Transport CVPR 2020 Interpolating between Optimal Transport and MMD using Sinkhorn Divergences AISTATS 2019 Sample Complexity of Sinkhorn Divergences AISTATS 2019 Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm NeurIPS 2019 Learning Generative Models with Sinkhorn Divergences AISTATS 2018