wasserstein distance

Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport NeurIPS 2018 Learning Generative Models with Sinkhorn Divergences AISTATS 2018 Learning semantic similarity in a continuous space NeurIPS 2018 Learning Wasserstein Embeddings ICLR 2018 Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance COLT 2018 Minimax Statistical Learning with Wasserstein distances NeurIPS 2018 Multi-Level Metric Learning via Smoothed Wasserstein Distance IJCAI 2018 Nonparametric Density Estimation under Adversarial Losses NeurIPS 2018 On the Convergence and Robustness of Training GANs with Regularized Optimal Transport NeurIPS 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 Robust Hypothesis Testing Using Wasserstein Uncertainty Sets NeurIPS 2018 Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018 Stochastic Wasserstein Barycenters ICML 2018 The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models NeurIPS 2018 Training GANs with Optimism ICLR 2018 Underdamped Langevin MCMC: A non-asymptotic analysis COLT 2018 Wasserstein Auto-Encoders ICLR 2018 Wasserstein Distributionally Robust Kalman Filtering NeurIPS 2018 Wasserstein Introspective Neural Networks CVPR 2018 Wasserstein Variational Inference NeurIPS 2018 Weakly Supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning IJCAI 2018 Which Training Methods for GANs do actually Converge? ICML 2018 A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization ICML 2017 Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering ACL 2017 Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent COLT 2017