Sampling with flows, diffusion and autoregressive neural networks: A
spin-glass perspective

Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective

27 August 2023

Florent Krzakala

Lenka Zdeborová

Papers citing "Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective"

7 / 7 papers shown

Title
Understanding Classifier-Free Guidance: High-Dimensional Theory and Non-Linear Generalizations Krunoslav Lehman Pavasovic Jakob Verbeek Giulio Biroli Marc Mézard 59 0 0 11 Feb 2025
Nonequilbrium physics of generative diffusion models Zhendong Yu Haiping Huang DiffM AI4CE 31 4 0 20 May 2024
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models Song Mei 3DV AI4CE DiffM 36 11 0 29 Apr 2024
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden DiffM 244 261 0 15 Mar 2023
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,774 0 24 Feb 2021
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 227 2,543 0 25 Jan 2016
Hiding Quiet Solutions in Random Constraint Satisfaction Problems Florent Krzakala Lenka Zdeborová 65 110 0 14 Jan 2009