Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples

9 February 2023

Papers citing "Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples"

5 / 5 papers shown

Title
Metrics that matter: Evaluating image quality metrics for medical image generation Yash Deo Yan Jia T. Lassila William A. P. Smith T. Lawton Siyuan Kang Alejandro F. Frangi Ibrahim Habli 34 0 0 12 May 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis Chen Gong Kecen Li Zinan Lin Tianhao Wang 47 3 0 18 Mar 2025
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction Jarrid Rector-Brooks Mohsin Hasan Zhangzhi Peng Zachary Quinn Chenghao Liu ... Michael Bronstein Yoshua Bengio Pranam Chatterjee Alexander Tong Avishek Joey Bose DiffM 42 6 0 10 Oct 2024
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 40 186 0 17 Feb 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,320 0 12 Dec 2018