wasserstein distance

Sliced Iterative Normalizing Flows ICML 2021 Smooth p-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications ICML 2021 Speech Enhancement with Topology-Enhanced Generative Adversarial Networks (GANs) Interspeech 2021 Supervised Tree-Wasserstein Distance ICML 2021 SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors AAAI 2021 Tighter Expected Generalization Error Bounds via Wasserstein Distance NeurIPS 2021 Towards Generalized Implementation of Wasserstein Distance in GANs AAAI 2021 Two-Sided Wasserstein Procrustes Analysis IJCAI 2021 Visual Transfer For Reinforcement Learning Via Wasserstein Domain Confusion AAAI 2021 Wasserstein Barycenter for Multi-Source Domain Adaptation CVPR 2021 Wasserstein Contrastive Representation Distillation CVPR 2021 Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations JMLR 2021 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data ICML 2021 Wasserstein Embedding for Graph Learning ICLR 2021 Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects AISTATS 2021 Wasserstein Selective Transfer Learning for Cross-domain Text Mining EMNLP 2021 When OT meets MoM: Robust estimation of Wasserstein Distance AISTATS 2021 AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection NeurIPS 2020 Approximate Inference with Wasserstein Gradient Flows AISTATS 2020 A Swiss Army Knife for Minimax Optimal Transport ICML 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NeurIPS 2020 A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions NeurIPS 2020 Bounding the expected run-time of nonconvex optimization with early stopping UAI 2020 Bridging the Gap Between f-GANs and Wasserstein GANs ICML 2020 Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks ICML 2020