U-Nets as Belief Propagation: Efficient Classification, Denoising, and
Diffusion in Generative Hierarchical Models

U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models

29 April 2024

Papers citing "U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models"

15 / 15 papers shown

Title
Learning curves theory for hierarchically compositional data with power-law distributed features Francesco Cagnetta Hyunmo Kang M. Wyart 12 0 0 11 May 2025
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures Francesco Cagnetta Alessandro Favero Antonio Sclocchi M. Wyart 9 0 0 11 May 2025
Physics-informed 4D X-ray image reconstruction from ultra-sparse spatiotemporal data Zisheng Yao Yuhe Zhang Zhe Hu Robert Klöfkorn Tobias Ritschel Pablo Villanueva-Perez AI4CE 58 1 0 04 Apr 2025
Probing the Latent Hierarchical Structure of Data via Diffusion Models Antonio Sclocchi Alessandro Favero Noam Itzhak Levi M. Wyart DiffM 23 1 0 17 Oct 2024
How transformers learn structured data: insights from hierarchical filtering Jerome Garnier-Brun Marc Mézard Emanuele Moscato Luca Saglietti 16 2 0 27 Aug 2024
Towards a theory of how the structure of language is acquired by deep neural networks Francesco Cagnetta M. Wyart 21 8 0 28 May 2024
Dynamical Regimes of Diffusion Models Giulio Biroli Tony Bonnaire Valentin De Bortoli Marc Mézard DiffM 34 40 0 28 Feb 2024
Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models Michael Celentano Zhou Fan Licong Lin Song Mei FedML 24 5 0 14 Nov 2023
Diffusion Models are Minimax Optimal Distribution Estimators Kazusato Oko Shunta Akiyama Taiji Suzuki DiffM 58 84 0 03 Mar 2023
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective Tanya Marwah Zachary Chase Lipton Jianfeng Lu Andrej Risteski 21 10 0 21 Oct 2022
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 174 128 0 26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 123 245 0 22 Sep 2022
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer Haonan Wang Peng Cao Jiaqi Wang Osmar R. Zaiane MedIm ViT 117 692 0 09 Sep 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding V. Papyan Yaniv Romano Michael Elad 48 283 0 27 Jul 2016