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

1

Talk (non-conference)

A statistical perspective on learning of time series in neural networks

Nestler, Sandra
2023

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

2

Poster

Information transfer between correlation functions in neural networks

Fischer, Kirsten
2023

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

3

Talk (non-conference)

Neural networks learning structure in temporal signals

Nestler, Sandra
2023

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

4

Poster

Neuronal extraction of statistical patterns embedded in time series

Nestler, Sandra
2023

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

5

Journal Article

Statistical temporal pattern extraction by neuronal architecture

Nestler, Sandra
2023

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

“...Transparent Deep Learning with Renormalized Flows...”
Get full text OpenAccess

6

Preprint

Optimal signal propagation in ResNets through residual scaling

Fischer, Kirsten
2023

“...Transparent Deep Learning with Renormalized Flows...”
Get full text OpenAccess

7

Poster

Optimal signal propagation in ResNets through residual scaling

Fischer, Kirsten
2023

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

8

Talk (non-conference)

Statistical Mechanics of Neural Networks

Fischer, Kirsten
2023

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

9

Poster

Residual scaling enables optimal signal propagation in ResNets

Fischer, Kirsten
2023

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

10

Poster

Nonlinear dimensionality reduction with normalizing flows for analysis of electrophysiological recordings

Bouss, Peter
2023

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

11

Poster

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

Fischer, Kirsten
2022

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

12

Talk (non-conference)

Tutorial on field theory of neuronal networks

Fischer, Kirsten
2022

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

13

Talk (non-conference)

Decomposing neural networks as mappings of correlation functions

Fischer, Kirsten
2022

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

14

Poster

Statistical decomposition of neural networks: Information transfer between correlation functions

Fischer, Kirsten
2022

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

15

Journal Article

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...”
OpenAccess OpenAccess

16

Preprint

Decomposing neural networks as mappings of correlation functions

Fischer, Kirsten
2022

“...Transparent Deep Learning with Renormalized Flows...”
Get full text OpenAccess

17

Poster

Unfolding recurrence by Green's functions for optimized reservoir computing

Nestler, Sandra
2022

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

18

Talk (non-conference)

Fluctuations, correlations, chaos: dynamics and computation in recurrent networks

Helias, Moritz
2021

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

19

Poster

Unfolding recurrence by Green’s functions for optimized reservoir computing

Nestler, Sandra
2021

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

20

Talk (non-conference)

Statistical physics approach to neuronal dynamics

van Meegen, Alexander
2021

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

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