"wasserstein distance" Papers
22 papers found
Conference
Assessing the quality of denoising diffusion models in Wasserstein distance: noisy score and optimal bounds
Vahan Arsenyan, Elen Vardanyan, Arnak Dalalyan
Bootstrap Your Uncertainty: Adaptive Robust Classification Driven by Optimal-Transport
Jiawei Huang, Minming Li, Hu Ding
Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning
Chongyi Zheng, Jens Tuyls, Joanne Peng et al.
Flow matching achieves almost minimax optimal convergence
Kenji Fukumizu, Taiji Suzuki, Noboru Isobe et al.
Non-convex entropic mean-field optimization via Best Response flow
Razvan-Andrei Lascu, Mateusz Majka
Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards
Kyungjae Lee, Dohyeong Kim, Taehyun Cho et al.
Self-Evolving Pseudo-Rehearsal for Catastrophic Forgetting with Task Similarity in LLMs
Jun Wang, Liang Ding, Shuai Wang et al.
Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
Megh Shukla, Aziz Shameem, Mathieu Salzmann et al.
Universal generalization guarantees for Wasserstein distributionally robust models
Tam Le, Jerome Malick
Wasserstein-Regularized Conformal Prediction under General Distribution Shift
Rui Xu, Chao Chen, Yue Sun et al.
ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models
Fei Kong, Jinhao Duan, Lichao Sun et al.
A New Robust Partial p-Wasserstein-Based Metric for Comparing Distributions
Sharath Raghvendra, Pouyan Shirzadian, Kaiyi Zhang
Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
Marta Catalano, Hugo Lavenant
MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations
Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz et al.
Optimal Transport for Structure Learning Under Missing Data
Vy Vo, He Zhao, Trung Le et al.
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
Junlong Lyu, Zhitang Chen, Shoubo Feng
Scalar Function Topology Divergence: Comparing Topology of 3D Objects
Ilya Trofimov, Daria Voronkova, Eduard Tulchinskii et al.
Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale, Viktor Bengs, Michele Caprio et al.
Standardized Interpretable Fairness Measures for Continuous Risk Scores
Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
Elen Vardanyan, Sona Hunanyan, Tigran Galstyan et al.
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling
Zehao Dou, Minshuo Chen, Mengdi Wang et al.