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ASDL: A Unified Interface for Gradient Preconditioning in PyTorch

ASDL: A Unified Interface for Gradient Preconditioning in PyTorch

8 May 2023
Kazuki Osawa
Satoki Ishikawa
Rio Yokota
Shigang Li
Torsten Hoefler
    ODL
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Papers citing "ASDL: A Unified Interface for Gradient Preconditioning in PyTorch"

13 / 13 papers shown
Title
Stein Variational Newton Neural Network Ensembles
Stein Variational Newton Neural Network Ensembles
Klemens Flöge
Mohammed Abdul Moeed
Vincent Fortuin
BDL
UQCV
37
0
0
04 Nov 2024
A New Perspective on Shampoo's Preconditioner
A New Perspective on Shampoo's Preconditioner
Depen Morwani
Itai Shapira
Nikhil Vyas
Eran Malach
Sham Kakade
Lucas Janson
35
7
0
25 Jun 2024
AdaFisher: Adaptive Second Order Optimization via Fisher Information
AdaFisher: Adaptive Second Order Optimization via Fisher Information
Damien Martins Gomes
Yanlei Zhang
Eugene Belilovsky
Guy Wolf
Mahdi S. Hosseini
ODL
76
2
0
26 May 2024
PETScML: Second-order solvers for training regression problems in
  Scientific Machine Learning
PETScML: Second-order solvers for training regression problems in Scientific Machine Learning
Stefano Zampini
Umberto Zerbinati
George Turkyyiah
David E. Keyes
43
4
0
18 Mar 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural
  Networks Using the Marginal Likelihood
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood
Rayen Dhahri
Alexander Immer
Bertrand Charpentier
Stephan Günnemann
Vincent Fortuin
BDL
UQCV
32
4
0
25 Feb 2024
Stochastic Hessian Fittings with Lie Groups
Stochastic Hessian Fittings with Lie Groups
Xi-Lin Li
40
1
0
19 Feb 2024
Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Curvature-Informed SGD via General Purpose Lie-Group Preconditioners
Omead Brandon Pooladzandi
Xi-Lin Li
38
4
0
07 Feb 2024
On the Parameterization of Second-Order Optimization Effective Towards
  the Infinite Width
On the Parameterization of Second-Order Optimization Effective Towards the Infinite Width
Satoki Ishikawa
Ryo Karakida
26
2
0
19 Dec 2023
Kronecker-Factored Approximate Curvature for Modern Neural Network
  Architectures
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Runa Eschenhagen
Alexander Immer
Richard Turner
Frank Schneider
Philipp Hennig
58
21
0
01 Nov 2023
The Memory Perturbation Equation: Understanding Model's Sensitivity to
  Data
The Memory Perturbation Equation: Understanding Model's Sensitivity to Data
Peter Nickl
Lu Xu
Dharmesh Tailor
Thomas Möllenhoff
Mohammad Emtiyaz Khan
24
10
0
30 Oct 2023
Bayesian Low-rank Adaptation for Large Language Models
Bayesian Low-rank Adaptation for Large Language Models
Adam X. Yang
Maxime Robeyns
Xi Wang
Laurence Aitchison
AI4CE
BDL
18
45
0
24 Aug 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Vincent Fortuin
BDL
UQCV
20
8
0
17 Apr 2023
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
268
0
13 Jun 2018
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