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Influence Functions for Scalable Data Attribution in Diffusion Models

17 October 2024

Papers citing "Influence Functions for Scalable Data Attribution in Diffusion Models"

38 / 38 papers shown

Title
Position: Curvature Matrices Should Be Democratized via Linear Operators Felix Dangel Runa Eschenhagen Weronika Ormaniec Andres Fernandez Lukas Tatzel Agustinus Kristiadi 122 4 0 31 Jan 2025
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models Jinxu Lin Linwei Tao Minjing Dong Chang Xu TDI 82 3 0 24 Oct 2024
Training Data Attribution via Approximate Unrolled Differentiation Juhan Bae Wu Lin Jonathan Lorraine Roger C. Grosse TDI MU 133 18 0 20 May 2024
Denoising Diffusion Probabilistic Models in Six Simple Steps Richard Turner Cristiana-Diana Diaconu Stratis Markou Aliaksandra Shysheya Andrew Y. K. Foong Bruno Mlodozeniec DiffM 50 6 0 06 Feb 2024
The Journey, Not the Destination: How Data Guides Diffusion Models Kristian Georgiev Joshua Vendrow Hadi Salman Sung Min Park Aleksander Madry 75 26 0 11 Dec 2023
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures Runa Eschenhagen Alexander Immer Richard Turner Frank Schneider Philipp Hennig 119 24 0 01 Nov 2023
Intriguing Properties of Data Attribution on Diffusion Models Xiaosen Zheng Tianyu Pang Chao Du Jing Jiang Min Lin TDI 109 26 1 01 Nov 2023
Generalization in diffusion models arises from geometry-adaptive harmonic representations Zahra Kadkhodaie Florentin Guth Eero P. Simoncelli Stéphane Mallat AI4CE DiffM 118 84 0 04 Oct 2023
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models Yongchan Kwon Eric Wu K. Wu James Zou DiffM TDI 88 68 0 02 Oct 2023
Studying Large Language Model Generalization with Influence Functions Roger C. Grosse Juhan Bae Cem Anil Nelson Elhage Alex Tamkin ... Karina Nguyen Nicholas Joseph Sam McCandlish Jared Kaplan Sam Bowman TDI 65 187 0 07 Aug 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc Aleksander Madry TDI 109 156 0 24 Mar 2023
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices Kazuki Osawa Shigang Li Torsten Hoefler AI4CE 76 25 0 25 Nov 2022
LAION-5B: An open large-scale dataset for training next generation image-text models Christoph Schuhmann Romain Beaumont Richard Vencu Cade Gordon Ross Wightman ... Srivatsa Kundurthy Katherine Crowson Ludwig Schmidt R. Kaczmarczyk J. Jitsev VLM MLLM CLIP 200 3,502 0 16 Oct 2022
If Influence Functions are the Answer, Then What is the Question? Juhan Bae Nathan Ng Alston Lo Marzyeh Ghassemi Roger C. Grosse TDI 95 104 0 12 Sep 2022
The ArtBench Dataset: Benchmarking Generative Models with Artworks Peiyuan Liao Xiuyu Li Xihui Liu Kurt Keutzer 70 49 0 22 Jun 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 97 48 0 22 Feb 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 499 15,788 0 20 Dec 2021
KAISA: An Adaptive Second-Order Optimizer Framework for Deep Neural Networks J. G. Pauloski Qi Huang Lei Huang Shivaram Venkataraman Kyle Chard Ian Foster Zhao-jie Zhang 60 29 0 04 Jul 2021
Variational Diffusion Models Diederik P. Kingma Tim Salimans Ben Poole Jonathan Ho DiffM 198 1,138 0 01 Jul 2021
LoRA: Low-Rank Adaptation of Large Language Models J. E. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen OffRL AI4TS AI4CE ALM AIMat 502 10,526 0 17 Jun 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 990 29,871 0 26 Feb 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 171 673 0 22 Jan 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 356 6,586 0 26 Nov 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 295 7,492 0 06 Oct 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 736 18,364 0 19 Jun 2020
On Second-Order Group Influence Functions for Black-Box Predictions S. Basu Xuchen You Soheil Feizi TDI 105 72 0 01 Nov 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,961 0 12 Jul 2019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model Guodong Zhang Lala Li Zachary Nado James Martens Sushant Sachdeva George E. Dahl Christopher J. Shallue Roger C. Grosse 107 154 0 09 Jul 2019
On the Accuracy of Influence Functions for Measuring Group Effects Pang Wei Koh Kai-Siang Ang H. Teo Percy Liang TDI 86 196 0 30 May 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent Frederik Kunstner Lukas Balles Philipp Hennig 88 219 0 29 May 2019
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis Thomas George César Laurent Xavier Bouthillier Nicolas Ballas Pascal Vincent ODL 84 156 0 11 Jun 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 800 132,454 0 12 Jun 2017
Practical Gauss-Newton Optimisation for Deep Learning Aleksandar Botev H. Ritter David Barber ODL 67 232 0 12 Jun 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 219 2,910 0 14 Mar 2017
A Kronecker-factored approximate Fisher matrix for convolution layers Roger C. Grosse James Martens ODL 108 264 0 03 Feb 2016
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger C. Grosse ODL 109 1,024 0 19 Mar 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
New insights and perspectives on the natural gradient method James Martens ODL 76 631 0 03 Dec 2014