wasserstein distance

Context Mover’s Distance & Barycenters: Optimal Transport of Contexts for Building Representations AISTATS 2020 Convergence Rate of Optimal Quantization and Application to the Clustering Performance of the Empirical Measure JMLR 2020 Cramer-Wold Auto-Encoder JMLR 2020 Debiased Sinkhorn barycenters ICML 2020 Deep Active Learning: Unified and Principled Method for Query and Training AISTATS 2020 Deep Diffusion-Invariant Wasserstein Distributional Classification NeurIPS 2020 Distributionally Robust Formulation and Model Selection for the Graphical Lasso AISTATS 2020 Distributional Robustness with IPMs and links to Regularization and GANs NeurIPS 2020 Double-Loop Unadjusted Langevin Algorithm ICML 2020 Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources ACL 2020 Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form NeurIPS 2020 Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine NeurIPS 2020 Faster Wasserstein Distance Estimation with the Sinkhorn Divergence NeurIPS 2020 FEW-SHOT LEARNING ON GRAPHS VIA SUPER-CLASSES BASED ON GRAPH SPECTRAL MEASURES ICLR 2020 GAIT: A Geometric Approach to Information Theory AISTATS 2020 Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency AISTATS 2020 Generating Realistic Stock Market Order Streams AAAI 2020 Hierarchically Robust Representation Learning CVPR 2020 Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning AAAI 2020 Learning Student Networks with Few Data AAAI 2020 Learning to Score Behaviors for Guided Policy Optimization ICML 2020 Lipschitz Continuous Autoencoders in Application to Anomaly Detection AISTATS 2020 Metric Learning in Optimal Transport for Domain Adaptation IJCAI 2020 Multiparameter Persistence Landscapes JMLR 2020 Multi-Source Distilling Domain Adaptation AAAI 2020