wasserstein distance

Computing Wasserstein-p Distance Between Images With Linear Cost CVPR 2022 Coordinate Linear Variance Reduction for Generalized Linear Programming NeurIPS 2022 Coresets for Wasserstein Distributionally Robust Optimization Problems NeurIPS 2022 Distributional Convergence of the Sliced Wasserstein Process NeurIPS 2022 Distributionally Robust Optimization with Data Geometry NeurIPS 2022 Efficient Sampling on Riemannian Manifolds via Langevin MCMC NeurIPS 2022 Entropic Gromov-Wasserstein between Gaussian Distributions ICML 2022 Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization AISTATS 2022 Fast topological clustering with Wasserstein distance ICLR 2022 Federated Functional Gradient Boosting AISTATS 2022 (f,Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics JMLR 2022 Flexible Accuracy for Differential Privacy AISTATS 2022 Generalization Bounds via Convex Analysis COLT 2022 Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization NeurIPS 2022 Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning NeurIPS 2022 Generative Modeling with Optimal Transport Maps ICLR 2022 GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction MLHC 2022 Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction ICLR 2022 High-Dimensional Projection Pursuit: Outer Bounds and Applications to Interpolation in Neural Networks COLT 2022 Integral Probability Metrics PAC-Bayes Bounds NeurIPS 2022 Intrinsic Dimension Estimation Using Wasserstein Distance JMLR 2022 Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? NeurIPS 2022 Latent Reweighting, an Almost Free Improvement for GANs WACV 2022 Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach ICLR 2022 Meta-learning without data via Wasserstein distributionally-robust model fusion UAI 2022