Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution

31 July 2023

Papers citing "Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution"

7 / 7 papers shown

Title
A Good Score Does not Lead to A Good Generative Model Sixu Li Shi Chen Qin Li DiffM 64 15 0 10 Jan 2024
Wasserstein GANs are Minimax Optimal Distribution Estimators Arthur Stéphanovitch Eddie Aamari Clément Levrard 20 2 0 30 Nov 2023
Riemannian Score-Based Generative Modelling Valentin De Bortoli Emile Mathieu M. Hutchinson James Thornton Yee Whye Teh Arnaud Doucet DiffM 209 163 0 06 Feb 2022
Rates of convergence for density estimation with generative adversarial networks Nikita Puchkin S. Samsonov Denis Belomestny Eric Moulines A. Naumov 17 5 0 30 Jan 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 267 1,798 0 14 Dec 2020
Statistical guarantees for generative models without domination Nicolas Schreuder Victor-Emmanuel Brunel A. Dalalyan GAN 54 34 0 19 Oct 2020
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model D. Gagne H. Christensen A. Subramanian A. Monahan AI4CE BDL 33 137 0 10 Sep 2019