Goldfeld, Ziv

22 publications

NeurIPS 2025 Estimation of Stochastic Optimal Transport Maps Sloan Nietert, Ziv Goldfeld

JMLR 2024 Entropic Gromov-Wasserstein Distances: Stability and Algorithms Gabriel Rioux, Ziv Goldfeld, Kengo Kato

NeurIPSW 2024 Neural Entropic Multimarginal Optimal Transport Dor Tsur, Ziv Goldfeld, Kristjan Greenewald, Haim H. Permuter

COLT 2024 Robust Distribution Learning with Local and Global Adversarial Corruptions (extended Abstract) Sloan Nietert, Ziv Goldfeld, Soroosh Shafiee

NeurIPSW 2023 Duality and Sample Complexity for the Gromov-Wasserstein Distance Zhengxin Zhang, Ziv Goldfeld, Youssef Mroueh, Bharath Sriperumbudur

NeurIPSW 2023 Entropic Gromov-Wasserstein Distances: Stability and Algorithms Gabriel Rioux, Ziv Goldfeld, Kengo Kato

NeurIPSW 2023 Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He, Christina Yu, Ziv Goldfeld

NeurIPS 2023 Max-Sliced Mutual Information Dor Tsur, Ziv Goldfeld, Kristjan Greenewald

NeurIPS 2023 Outlier-Robust Wasserstein DRO Sloan Nietert, Ziv Goldfeld, Soroosh Shafiee

NeurIPSW 2023 Outlier-Robust Wasserstein DRO Sloan Nietert, Ziv Goldfeld, Soroosh Shafieezadeh-Abadeh

NeurIPSW 2023 Semi-Discrete Gromov-Wasserstein Distances: Existence of Gromov-Monge Maps and Statistical Theory Gabriel Rioux, Ziv Goldfeld, Kengo Kato

AISTATS 2022 Cycle Consistent Probability Divergences Across Different Spaces Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath Sriperumbudur

AISTATS 2022 Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis Sloan Nietert, Ziv Goldfeld, Rachel Cummings

NeurIPS 2022 $k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension Ziv Goldfeld, Kristjan Greenewald, Theshani Nuradha, Galen Reeves

JMLR 2022 Neural Estimation of Statistical Divergences Sreejith Sreekumar, Ziv Goldfeld

NeurIPS 2022 Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances Sloan Nietert, Ziv Goldfeld, Ritwik Sadhu, Kengo Kato

AISTATS 2021 Non-Asymptotic Performance Guarantees for Neural Estimation of F-Divergences Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld

NeurIPS 2021 Sliced Mutual Information: A Scalable Measure of Statistical Dependence Ziv Goldfeld, Kristjan Greenewald

ICML 2021 Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications Sloan Nietert, Ziv Goldfeld, Kengo Kato

NeurIPS 2020 Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance Ziv Goldfeld, Kristjan Greenewald, Kengo Kato

AISTATS 2020 Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency Ziv Goldfeld, Kristjan Greenewald

ICML 2019 Estimating Information Flow in Deep Neural Networks Ziv Goldfeld, Ewout Van Den Berg, Kristjan Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, Yury Polyanskiy