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Function approximation by neural nets in the mean-field regime: Entropic
  regularization and controlled McKean-Vlasov dynamics

Function approximation by neural nets in the mean-field regime: Entropic regularization and controlled McKean-Vlasov dynamics

5 February 2020
Belinda Tzen
Maxim Raginsky
ArXivPDFHTML

Papers citing "Function approximation by neural nets in the mean-field regime: Entropic regularization and controlled McKean-Vlasov dynamics"

3 / 3 papers shown
Title
Convex Analysis of the Mean Field Langevin Dynamics
Convex Analysis of the Mean Field Langevin Dynamics
Atsushi Nitanda
Denny Wu
Taiji Suzuki
MLT
68
64
0
25 Jan 2022
Non-asymptotic approximations of neural networks by Gaussian processes
Non-asymptotic approximations of neural networks by Gaussian processes
Ronen Eldan
Dan Mikulincer
T. Schramm
35
24
0
17 Feb 2021
Predicting the outputs of finite deep neural networks trained with noisy
  gradients
Predicting the outputs of finite deep neural networks trained with noisy gradients
Gadi Naveh
Oded Ben-David
H. Sompolinsky
Zohar Ringel
16
20
0
02 Apr 2020
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