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Probing the Latent Hierarchical Structure of Data via Diffusion Models

17 October 2024

Papers citing "Probing the Latent Hierarchical Structure of Data via Diffusion Models"

41 / 41 papers shown

Title
On the Emergence of Linear Analogies in Word Embeddings Daniel J. Korchinski Dhruva Karkada Yasaman Bahri Matthieu Wyart 50 0 0 24 May 2025
Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Models Alessandro Favero Antonio Sclocchi Matthieu Wyart DiffM 51 0 0 22 May 2025
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures Francesco Cagnetta Alessandro Favero Antonio Sclocchi Matthieu Wyart 74 0 0 11 May 2025
Learning curves theory for hierarchically compositional data with power-law distributed features Francesco Cagnetta Hyunmo Kang Matthieu Wyart 115 1 0 11 May 2025
How Compositional Generalization and Creativity Improve as Diffusion Models are Trained Alessandro Favero Antonio Sclocchi Francesco Cagnetta Pascal Frossard Matthieu Wyart DiffM CoGe 83 6 0 17 Feb 2025
Avoiding mode collapse in diffusion models fine-tuned with reinforcement learning Roberto Barceló Cristóbal Alcázar Felipe Tobar 77 4 0 10 Oct 2024
How transformers learn structured data: insights from hierarchical filtering Jerome Garnier-Brun Marc Mézard Emanuele Moscato Luca Saglietti 134 6 0 27 Aug 2024
Simple and Effective Masked Diffusion Language Models Subham Sekhar Sahoo Marianne Arriola Yair Schiff Aaron Gokaslan Edgar Marroquin Justin T Chiu Alexander M. Rush Volodymyr Kuleshov DiffM 106 122 0 11 Jun 2024
Towards a theory of how the structure of language is acquired by deep neural networks Francesco Cagnetta Matthieu Wyart 65 10 0 28 May 2024
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models Song Mei 3DV AI4CE DiffM 64 13 0 29 Apr 2024
Critical windows: non-asymptotic theory for feature emergence in diffusion models Marvin Li Sitan Chen DiffM 88 14 0 03 Mar 2024
Dynamical Regimes of Diffusion Models Giulio Biroli Tony Bonnaire Valentin De Bortoli Marc Mézard DiffM 102 56 0 28 Feb 2024
A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data Antonio Sclocchi Alessandro Favero Matthieu Wyart DiffM 86 37 0 26 Feb 2024
The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability Luca Ambrogioni AI4CE DiffM 85 20 0 26 Oct 2023
U-Turn Diffusion Hamidreza Behjoo Michael Chertkov 53 3 0 14 Aug 2023
How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model Francesco Cagnetta Leonardo Petrini Umberto M. Tomasini Alessandro Favero Matthieu Wyart BDL 93 26 0 05 Jul 2023
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning Wenliang Dai Junnan Li Dongxu Li A. M. H. Tiong Junqi Zhao Weisheng Wang Boyang Albert Li Pascale Fung Steven C. H. Hoi MLLM VLM 139 2,095 0 11 May 2023
Visual Instruction Tuning Haotian Liu Chunyuan Li Qingyang Wu Yong Jae Lee SyDa VLM MLLM 571 4,910 0 17 Apr 2023
Learning multi-scale local conditional probability models of images Zahra Kadkhodaie Florentin Guth S. Mallat Eero P. Simoncelli DiffM 85 19 0 06 Mar 2023
Diffusion Models Generate Images Like Painters: an Analytical Theory of Outline First, Details Later Binxu Wang John J. Vastola DiffM 162 27 0 04 Mar 2023
LLaMA: Open and Efficient Foundation Language Models Hugo Touvron Thibaut Lavril Gautier Izacard Xavier Martinet Marie-Anne Lachaux ... Faisal Azhar Aurelien Rodriguez Armand Joulin Edouard Grave Guillaume Lample ALM PILM 1.5K 13,472 0 27 Feb 2023
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Tengjiao Wang Ming-Hsuan Yang DiffM MedIm 411 1,407 0 02 Sep 2022
Generative Modelling With Inverse Heat Dissipation Severi Rissanen Markus Heinonen Arno Solin DiffM 90 118 0 21 Jun 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 886 13,207 0 04 Mar 2022
A ConvNet for the 2020s Zhuang Liu Hanzi Mao Chaozheng Wu Christoph Feichtenhofer Trevor Darrell Saining Xie ViT 186 5,213 0 10 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 496 15,768 0 20 Dec 2021
Structured Denoising Diffusion Models in Discrete State-Spaces Jacob Austin Daniel D. Johnson Jonathan Ho Daniel Tarlow Rianne van den Berg DiffM 185 948 0 07 Jul 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 981 29,871 0 26 Feb 2021
Improved Denoising Diffusion Probabilistic Models Alex Nichol Prafulla Dhariwal DiffM 352 3,716 0 18 Feb 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 353 6,586 0 26 Nov 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 724 18,364 0 19 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 882 42,463 0 28 May 2020
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,961 0 12 Jul 2019
A Provably Correct Algorithm for Deep Learning that Actually Works Eran Malach Shai Shalev-Shwartz MLT 114 31 0 26 Mar 2018
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 238 816 0 22 Aug 2017
Failures of Gradient-Based Deep Learning Shai Shalev-Shwartz Ohad Shamir Shaked Shammah ODL UQCV 109 201 0 23 Mar 2017
Deep Learning and Hierarchal Generative Models Elchanan Mossel BDL GAN 109 24 0 29 Dec 2016
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review T. Poggio H. Mhaskar Lorenzo Rosasco Brando Miranda Q. Liao 143 576 0 02 Nov 2016
A Probabilistic Theory of Deep Learning Ankit B. Patel M. T. Nguyen Richard G. Baraniuk BDL OOD UQCV 85 89 0 02 Apr 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 312 7,031 0 12 Mar 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 184 706 0 30 Dec 2014