ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2312.05705
  4. Cited By
Structured Inverse-Free Natural Gradient: Memory-Efficient &
  Numerically-Stable KFAC

Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC

9 December 2023
Wu Lin
Felix Dangel
Runa Eschenhagen
Kirill Neklyudov
Agustinus Kristiadi
Richard E. Turner
Alireza Makhzani
ArXivPDFHTML

Papers citing "Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC"

5 / 5 papers shown
Title
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
48
3
0
31 Jan 2025
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
21
6
0
24 May 2024
Thermodynamic Natural Gradient Descent
Thermodynamic Natural Gradient Descent
Kaelan Donatella
Samuel Duffield
Maxwell Aifer
Denis Melanson
Gavin Crooks
Patrick J. Coles
26
3
0
22 May 2024
Patches Are All You Need?
Patches Are All You Need?
Asher Trockman
J. Zico Kolter
ViT
214
400
0
24 Jan 2022
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
74
266
0
13 Jun 2018
1