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Exploring the Function Space of Deep-Learning Machines
4 August 2017
Yue Liu
D. Saad
PINN
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Papers citing
"Exploring the Function Space of Deep-Learning Machines"
13 / 13 papers shown
Dynamics of Meta-learning Representation in the Teacher-student Scenario
Physical Review E (Phys. Rev. E), 2024
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Cho Tung Yip
Bo Li
377
1
0
22 Aug 2024
Exploring Loss Landscapes through the Lens of Spin Glass Theory
Hao Liao
Wei Zhang
Zhanyi Huang
Zexiao Long
Mingyang Zhou
Xiaoqun Wu
Rui Mao
Chi Ho Yeung
307
3
0
30 Jul 2024
A random energy approach to deep learning
Rongrong Xie
M. Marsili
FedML
121
6
0
17 Dec 2021
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise
Nidhin Harilal
Udit Bhatia
A. Ganguly
OOD
148
0
0
23 Jun 2021
Initializing ReLU networks in an expressive subspace of weights
Dayal Singh
J. SreejithG
238
4
0
23 Mar 2021
No one-hidden-layer neural network can represent multivariable functions
Masayo Inoue
Mana Futamura
H. Ninomiya
MLT
83
0
0
19 Jun 2020
Beyond the storage capacity: data driven satisfiability transition
P. Rotondo
M. Pastore
M. Gherardi
121
18
0
20 May 2020
Space of Functions Computed by Deep-Layered Machines
Alexander Mozeika
Bo Li
D. Saad
251
8
0
19 Apr 2020
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
420
37
0
03 Nov 2019
Large Deviation Analysis of Function Sensitivity in Random Deep Neural Networks
Bo Li
D. Saad
159
12
0
13 Oct 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation
Greg Yang
665
303
0
13 Feb 2019
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida
S. Akaho
S. Amari
FedML
676
169
0
04 Jun 2018
A high-bias, low-variance introduction to Machine Learning for physicists
Pankaj Mehta
Marin Bukov
Ching-Hao Wang
A. G. Day
C. Richardson
Charles K. Fisher
D. Schwab
AI4CE
447
972
0
23 Mar 2018
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