Co-occurring keywords · papers mentioning both
Papers
Deep Kernel Relative Test for Machine-generated Text Detection
ICLR 2025
Global Ground Metric Learning with Applications to scRNA data
AISTATS 2025
Data Distribution Valuation
NeurIPS 2024
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions
NeurIPS 2024
Validating Climate Models with Spherical Convolutional Wasserstein Distance
NeurIPS 2024
Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe
AISTATS 2022
Fixed Support Tree-Sliced Wasserstein Barycenter
AISTATS 2022
Two-Sample Test with Kernel Projected Wasserstein Distance
AISTATS 2022
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
NeurIPS 2021
Deep Divergence Learning
ICML 2020
Comparing distributions: ℓ_1 geometry improves kernel two-sample testing
NeurIPS 2019
Sliced Gromov-Wasserstein
NeurIPS 2019
Learning Wasserstein Embeddings
ICLR 2018
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
NeurIPS 2015
A Kernel Two-Sample Test
JMLR 2012
Density-Difference Estimation
NeurIPS 2012
Optimal kernel choice for large-scale two-sample tests
NeurIPS 2012
Relative Density-Ratio Estimation for Robust Distribution Comparison
NeurIPS 2011
A Kernel Method for the Two-Sample-Problem
NeurIPS 2006