conftrace_

wasserstein metric

29 papers

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Co-occurring keywords

optimal transport (948) wasserstein distance (417) generative model (2892) distributionally robust optimization (185) gradient flow (142) generative adversarial network (1944) neural network (6616) convolutional neural network (4226) convergence rate (607) maximum mean discrepancy (164)

Papers

Dataset Distillation via the Wasserstein Metric ICCV 2025
Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling JMLR 2024
Interaction-Force Transport Gradient Flows NIPS 2024
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport AISTATS 2024
Bures-Wasserstein Means of Graphs AISTATS 2024
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent NIPS 2023
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation NIPS 2023
Rate of Convergence of Polynomial Networks to Gaussian Processes COLT 2022
Sinkformers: Transformers with Doubly Stochastic Attention AISTATS 2022
Projected Statistical Methods for Distributional Data on the Real Line with the Wasserstein Metric JMLR 2022
Conditional Loss and Deep Euler Scheme for Time Series Generation AAAI 2022
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime ICML 2022
Wasserstein $K$-means for clustering probability distributions NIPS 2022
Beyond black box densities: Parameter learning for the deviated components NIPS 2022
Multi-Proxy Wasserstein Classifier for Image Classification AAAI 2021
Moreau-Yosida $f$-divergences ICML 2021
Self-Supervised Wasserstein Pseudo-Labeling for Semi-Supervised Image Classification CVPR 2021
Wasserstein Distributionally Robust Inverse Multiobjective Optimization AAAI 2021
Projection Robust Wasserstein Barycenters ICML 2021
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation CVPR 2019
Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression NIPS 2019
A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization JMLR 2018
Representing and Learning High Dimensional Data With the Optimal Transport Map From a Probabilistic Viewpoint CVPR 2018
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions NIPS 2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets NIPS 2018