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ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure
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ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure

Felix Dangel
Lukas Tatzel
Philipp Hennig
ArXiv (abs)PDFHTML

Papers citing "ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure"

10 / 10 papers shown
Title
Connecting Parameter Magnitudes and Hessian Eigenspaces at Scale using Sketched Methods
Connecting Parameter Magnitudes and Hessian Eigenspaces at Scale using Sketched Methods
Andres Fernandez
Frank Schneider
Maren Mahsereci
Philipp Hennig
118
0
0
20 Apr 2025
Position: Curvature Matrices Should Be Democratized via Linear Operators
Position: Curvature Matrices Should Be Democratized via Linear Operators
Felix Dangel
Runa Eschenhagen
Weronika Ormaniec
Andres Fernandez
Lukas Tatzel
Agustinus Kristiadi
135
4
0
31 Jan 2025
TrAct: Making First-layer Pre-Activations Trainable
TrAct: Making First-layer Pre-Activations Trainable
Felix Petersen
Christian Borgelt
Stefano Ermon
68
0
0
31 Oct 2024
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Tatzel
Bálint Mucsányi
Osane Hackel
Philipp Hennig
115
0
0
18 Oct 2024
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
Emilia Magnani
Marvin Pfortner
Tobias Weber
Philipp Hennig
UQCV
131
1
0
07 Jun 2024
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed
Homayoon Farrahi
Felix Dangel
A. Rupam Mahmood
66
4
0
05 Jun 2024
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Felix Dangel
Johannes Müller
Marius Zeinhofer
ODL
107
11
0
24 May 2024
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data
Mike He Zhu
Léna Néhale Ezzine
Dianbo Liu
Yoshua Bengio
OODFedML
53
5
0
19 May 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization
Frederik Benzing
ODL
127
26
0
28 Jan 2022
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Ramé
Corentin Dancette
Matthieu Cord
OOD
146
210
0
07 Sep 2021

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