$Non-Asymptotic Performance Guarantees for Neural Estimation of $\mathsf{f}$-Divergences$

Non-Asymptotic Performance Guarantees for Neural Estimation of $\mathsf{f}$ -Divergences

11 March 2021

Sreejith Sreekumar

Papers citing "Non-Asymptotic Performance Guarantees for Neural Estimation of $\mathsf{f}$-Divergences"

12 / 12 papers shown

Title
Lower Bounds on the MMSE of Adversarially Inferring Sensitive Features Monica Welfert Nathan Stromberg Mario Díaz Lalitha Sankar AAML 14 0 0 13 May 2025
Learning heavy-tailed distributions with Wasserstein-proximal-regularized $α$ -divergences Ziyu Chen Hyemin Gu M. Katsoulakis Luc Rey-Bellet Wei-wei Zhu 34 0 0 22 May 2024
Neural Estimation Of Entropic Optimal Transport Tao Wang Ziv Goldfeld OT 36 1 0 10 May 2024
Limit Distribution Theory for Quantum Divergences Sreejith Sreekumar Mario Berta 23 2 0 22 Nov 2023
Max-Sliced Mutual Information Dor Tsur Ziv Goldfeld Kristjan Greenewald 32 9 0 28 Sep 2023
Quantum Neural Estimation of Entropies Ziv Goldfeld Dhrumil Patel Sreejith Sreekumar Mark M. Wilde 30 9 0 03 Jul 2023
Energy-guided Entropic Neural Optimal Transport Petr Mokrov Alexander Korotin Alexander Kolesov Nikita Gushchin Evgeny Burnaev OT 51 21 0 12 Apr 2023
Data-Driven Optimization of Directed Information over Discrete Alphabets Dor Tsur Ziv Aharoni Ziv Goldfeld H. Permuter 25 9 0 02 Jan 2023
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension Ziv Goldfeld Kristjan Greenewald Theshani Nuradha Galen Reeves 31 0 0 17 Jun 2022
Certifying Out-of-Domain Generalization for Blackbox Functions Maurice Weber Linyi Li Boxin Wang Zhikuan Zhao Bo-wen Li Ce Zhang OOD 21 14 0 03 Feb 2022
Fast approximations of the Jeffreys divergence between univariate Gaussian mixture models via exponential polynomial densities Frank Nielsen 35 12 0 13 Jul 2021
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals Lang Liu Krishna Pillutla Sean Welleck Sewoong Oh Yejin Choi Zaïd Harchaoui MQ 25 14 0 15 Jun 2021