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Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean
  Field Neural Networks

Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks

6 April 2023
Blake Bordelon
C. Pehlevan
    MLT
ArXivPDFHTML

Papers citing "Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks"

25 / 25 papers shown
Title
Don't be lazy: CompleteP enables compute-efficient deep transformers
Don't be lazy: CompleteP enables compute-efficient deep transformers
Nolan Dey
Bin Claire Zhang
Lorenzo Noci
Mufan Bill Li
Blake Bordelon
Shane Bergsma
C. Pehlevan
Boris Hanin
Joel Hestness
37
0
0
02 May 2025
Uncertainty Quantification From Scaling Laws in Deep Neural Networks
Ibrahim Elsharkawy
Yonatan Kahn
Benjamin Hooberman
UQCV
45
0
0
07 Mar 2025
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Samet Demir
Zafer Dogan
MLT
34
0
0
02 Mar 2025
Function-Space Learning Rates
Edward Milsom
Ben Anson
Laurence Aitchison
41
1
0
24 Feb 2025
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Dayal Singh Kalra
Tianyu He
M. Barkeshli
47
4
0
17 Feb 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon
C. Pehlevan
AI4CE
59
1
0
04 Feb 2025
The Optimization Landscape of SGD Across the Feature Learning Strength
The Optimization Landscape of SGD Across the Feature Learning Strength
Alexander B. Atanasov
Alexandru Meterez
James B. Simon
C. Pehlevan
43
2
0
06 Oct 2024
Bayesian RG Flow in Neural Network Field Theories
Bayesian RG Flow in Neural Network Field Theories
Jessica N. Howard
Marc S. Klinger
Anindita Maiti
A. G. Stapleton
60
1
0
27 May 2024
Dissecting the Interplay of Attention Paths in a Statistical Mechanics
  Theory of Transformers
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
Lorenzo Tiberi
Francesca Mignacco
Kazuki Irie
H. Sompolinsky
39
5
0
24 May 2024
Infinite Limits of Multi-head Transformer Dynamics
Infinite Limits of Multi-head Transformer Dynamics
Blake Bordelon
Hamza Tahir Chaudhry
C. Pehlevan
AI4CE
35
9
0
24 May 2024
Asymptotics of feature learning in two-layer networks after one
  gradient-step
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui
Luca Pesce
Yatin Dandi
Florent Krzakala
Yue M. Lu
Lenka Zdeborová
Bruno Loureiro
MLT
44
16
0
07 Feb 2024
A Dynamical Model of Neural Scaling Laws
A Dynamical Model of Neural Scaling Laws
Blake Bordelon
Alexander B. Atanasov
C. Pehlevan
44
36
0
02 Feb 2024
More is Better in Modern Machine Learning: when Infinite
  Overparameterization is Optimal and Overfitting is Obligatory
More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James B. Simon
Dhruva Karkada
Nikhil Ghosh
Mikhail Belkin
AI4CE
BDL
18
13
0
24 Nov 2023
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and
  Scaling Limit
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Blake Bordelon
Lorenzo Noci
Mufan Bill Li
Boris Hanin
C. Pehlevan
14
22
0
28 Sep 2023
Small-scale proxies for large-scale Transformer training instabilities
Small-scale proxies for large-scale Transformer training instabilities
Mitchell Wortsman
Peter J. Liu
Lechao Xiao
Katie Everett
A. Alemi
...
Jascha Narain Sohl-Dickstein
Kelvin Xu
Jaehoon Lee
Justin Gilmer
Simon Kornblith
30
80
0
25 Sep 2023
Speed Limits for Deep Learning
Speed Limits for Deep Learning
Inbar Seroussi
Alexander A. Alemi
M. Helias
Z. Ringel
11
0
0
27 Jul 2023
Neural Network Field Theories: Non-Gaussianity, Actions, and Locality
Neural Network Field Theories: Non-Gaussianity, Actions, and Locality
M. Demirtaş
James Halverson
Anindita Maiti
M. Schwartz
Keegan Stoner
AI4CE
16
10
0
06 Jul 2023
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Yatin Dandi
Florent Krzakala
Bruno Loureiro
Luca Pesce
Ludovic Stephan
MLT
27
25
0
29 May 2023
Feature-Learning Networks Are Consistent Across Widths At Realistic
  Scales
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
Nikhil Vyas
Alexander B. Atanasov
Blake Bordelon
Depen Morwani
Sabarish Sainathan
C. Pehlevan
17
22
0
28 May 2023
Phase diagram of early training dynamics in deep neural networks: effect
  of the learning rate, depth, and width
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
Dayal Singh Kalra
M. Barkeshli
11
9
0
23 Feb 2023
Meta-Principled Family of Hyperparameter Scaling Strategies
Meta-Principled Family of Hyperparameter Scaling Strategies
Sho Yaida
50
16
0
10 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural
  Networks
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
Blake Bordelon
C. Pehlevan
38
22
0
05 Oct 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide
  Neural Networks
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
Blake Bordelon
C. Pehlevan
MLT
17
78
0
19 May 2022
The large learning rate phase of deep learning: the catapult mechanism
The large learning rate phase of deep learning: the catapult mechanism
Aitor Lewkowycz
Yasaman Bahri
Ethan Dyer
Jascha Narain Sohl-Dickstein
Guy Gur-Ari
ODL
150
232
0
04 Mar 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural
  Networks
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon
Abdulkadir Canatar
C. Pehlevan
131
199
0
07 Feb 2020
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