JuLib | Articles & more - {"Transparent Deep Learning with Renormalized Flows"}

Gell-Mann-Low criticality in neural networks

Tiberi, Lorenzo
2023

“...Transparent Deep Learning with Renormalized Flows...”

2

Optimal signal propagation in ResNets through residual scaling

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”

3

Statistical Mechanics of Neural Networks

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”

4

Residual scaling enables optimal signal propagation in ResNets

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”

5

A statistical perspective on learning of time series in neural networks

Nestler, Sandra
2023

“...Transparent Deep Learning with Renormalized Flows...”

6

Information transfer between correlation functions in neural networks

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”

7

Nonlinear dimensionality reduction with normalizing flows for analysis of electrophysiological recordings

Bouss, Peter
2023

“...Transparent Deep Learning with Renormalized Flows...”
OpenAccess

8

Linking Network and Neuron Level Correlations via Renormalized Field Theory

Dick, Michael
2023

“...Transparent Deep Learning with Renormalized Flows...”
OpenAccess

9

Preprint

Optimal signal propagation in ResNets through residual scaling

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”
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10

Statistical temporal pattern extraction by neuronal architecture

Nestler, Sandra
2023

Physical review research, 5 (2023) 3, S. 033177

“...Transparent Deep Learning with Renormalized Flows...”
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11

Neuronal extraction of statistical patterns embedded in time series

Nestler, Sandra
2023

“...Transparent Deep Learning with Renormalized Flows...”

12

Neural networks learning structure in temporal signals

Nestler, Sandra
2023

“...Transparent Deep Learning with Renormalized Flows...”

13

Statistical decomposition of neural networks: Information transfer between correlation functions

Fischer, Kirsten
2022

“...Transparent Deep Learning with Renormalized Flows...”

14

Preprint

Phase Space Analysis of Chaotic Neural Networks

Stubenrauch, Jakob
2022

“...Transparent Deep Learning with Renormalized Flows...”
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15

Decomposing neural networks as mappings of correlation functions

Fischer, Kirsten
2022

Physical review research, 4 (2022) 4, S. 043143

“...Transparent Deep Learning with Renormalized Flows...”
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16

Preprint

Decomposing neural networks as mappings of correlation functions

Fischer, Kirsten
2022

“...Transparent Deep Learning with Renormalized Flows...”
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17

Statistical decomposition of feed-forward neural networks: Transfer of information between correlation functions

Fischer, Kirsten
2022

“...Transparent Deep Learning with Renormalized Flows...”

18

Tutorial on field theory of neuronal networks

Fischer, Kirsten
2022

“...Transparent Deep Learning with Renormalized Flows...”

19

Gell-Mann–Low Criticality in Neural Networks

Tiberi, Lorenzo
2022

Physical review letters, 128 (2022) 16, S. 168301

“...Transparent Deep Learning with Renormalized Flows...”
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