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2410.13850
Cited By
Influence Functions for Scalable Data Attribution in Diffusion Models
17 October 2024
Bruno Mlodozeniec
Runa Eschenhagen
Juhan Bae
Alexander Immer
David Krueger
Richard E. Turner
DiffM
TDI
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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
102
3
0
31 Jan 2025
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
Jinxu Lin
Linwei Tao
Minjing Dong
Chang Xu
TDI
65
3
0
24 Oct 2024
Training Data Attribution via Approximate Unrolled Differentiation
Juhan Bae
Wu Lin
Jonathan Lorraine
Roger C. Grosse
TDI
MU
112
16
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
41
5
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
61
25
0
11 Dec 2023
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Runa Eschenhagen
Alexander Immer
Richard Turner
Frank Schneider
Philipp Hennig
112
23
0
01 Nov 2023
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng
Tianyu Pang
Chao Du
Jing Jiang
Min Lin
TDI
77
25
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
96
81
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
73
66
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
46
181
0
07 Aug 2023
TRAK: Attributing Model Behavior at Scale
Sung Min Park
Kristian Georgiev
Andrew Ilyas
Guillaume Leclerc
Aleksander Madry
TDI
74
150
0
24 Mar 2023
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices
Kazuki Osawa
Shigang Li
Torsten Hoefler
AI4CE
50
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
139
3,438
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
54
97
0
12 Sep 2022
The ArtBench Dataset: Benchmarking Generative Models with Artworks
Peiyuan Liao
Xiuyu Li
Xihui Liu
Kurt Keutzer
54
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
74
48
0
22 Feb 2022
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach
A. Blattmann
Dominik Lorenz
Patrick Esser
Bjorn Ommer
3DV
378
15,454
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
52
29
0
04 Jul 2021
Variational Diffusion Models
Diederik P. Kingma
Tim Salimans
Ben Poole
Jonathan Ho
DiffM
157
1,117
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
373
10,273
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
830
29,341
0
26 Feb 2021
Maximum Likelihood Training of Score-Based Diffusion Models
Yang Song
Conor Durkan
Iain Murray
Stefano Ermon
DiffM
129
663
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
308
6,444
0
26 Nov 2020
Denoising Diffusion Implicit Models
Jiaming Song
Chenlin Meng
Stefano Ermon
VLM
DiffM
216
7,350
0
06 Oct 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
535
18,008
0
19 Jun 2020
On Second-Order Group Influence Functions for Black-Box Predictions
S. Basu
Xuchen You
Soheil Feizi
TDI
73
69
0
01 Nov 2019
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDa
DiffM
216
3,893
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
90
152
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
66
190
0
30 May 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent
Frederik Kunstner
Lukas Balles
Philipp Hennig
70
216
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
67
153
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
660
131,414
0
12 Jun 2017
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev
H. Ritter
David Barber
ODL
49
231
0
12 Jun 2017
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
169
2,882
0
14 Mar 2017
A Kronecker-factored approximate Fisher matrix for convolution layers
Roger C. Grosse
James Martens
ODL
102
261
0
03 Feb 2016
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
James Martens
Roger C. Grosse
ODL
95
1,011
0
19 Mar 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
274
6,925
0
12 Mar 2015
New insights and perspectives on the natural gradient method
James Martens
ODL
69
623
0
03 Dec 2014
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