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Unified field theoretical approach to deep and recurrent neuronal
  networks

Unified field theoretical approach to deep and recurrent neuronal networks

10 December 2021
Kai Segadlo
Bastian Epping
Alexander van Meegen
David Dahmen
Michael Krämer
M. Helias
    AI4CE
    BDL
ArXivPDFHTML

Papers citing "Unified field theoretical approach to deep and recurrent neuronal networks"

3 / 3 papers shown
Title
A theory of data variability in Neural Network Bayesian inference
A theory of data variability in Neural Network Bayesian inference
Javed Lindner
David Dahmen
Michael Krämer
M. Helias
BDL
32
1
0
31 Jul 2023
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
Blake Bordelon
Cengiz Pehlevan
MLT
38
29
0
06 Apr 2023
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
Cengiz Pehlevan
MLT
40
77
0
19 May 2022
1