probability measure

On Transportation of Mini-batches: A Hierarchical Approach ICML 2022 Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution NeurIPS 2022 Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics AISTATS 2022 Supervised Training of Conditional Monge Maps NeurIPS 2022 A Functional Perspective on Learning Symmetric Functions with Neural Networks ICML 2021 Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization ICLR 2021 Distributional Sliced-Wasserstein and Applications to Generative Modeling ICLR 2021 Entropy Partial Transport with Tree Metrics: Theory and Practice AISTATS 2021 Fast and Smooth Interpolation on Wasserstein Space AISTATS 2021 FFT-OT: A Fast Algorithm for Optimal Transportation ICCV 2021 Flow-based Alignment Approaches for Probability Measures in Different Spaces AISTATS 2021 Improving approximate optimal transport distances using quantization UAI 2021 Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks COLT 2021 Modified Frank Wolfe in Probability Space NeurIPS 2021 On efficient multilevel Clustering via Wasserstein distances JMLR 2021 Bayesian Meta Sampling for Fast Uncertainty Adaptation ICLR 2020 Deep Diffusion-Invariant Wasserstein Distributional Classification NeurIPS 2020 Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm NeurIPS 2020 Gradient descent algorithms for Bures-Wasserstein barycenters COLT 2020 Projection Robust Wasserstein Distance and Riemannian Optimization NeurIPS 2020 Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space AISTATS 2020 Riemannian Continuous Normalizing Flows NeurIPS 2020 Sinkhorn Natural Gradient for Generative Models NeurIPS 2020 Synchronizing Probability Measures on Rotations via Optimal Transport CVPR 2020 Elliptical Perturbations for Differential Privacy NeurIPS 2019