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Using activation histograms to bound the number of affine regions in
  ReLU feed-forward neural networks

Using activation histograms to bound the number of affine regions in ReLU feed-forward neural networks

31 March 2021
Peter Hinz
ArXivPDFHTML

Papers citing "Using activation histograms to bound the number of affine regions in ReLU feed-forward neural networks"

4 / 4 papers shown
Title
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
94
33
0
29 Apr 2023
The Power of Typed Affine Decision Structures: A Case Study
The Power of Typed Affine Decision Structures: A Case Study
Gerrit Nolte
Maximilian Schlüter
Alnis Murtovi
Bernhard Steffen
AAML
20
3
0
28 Apr 2023
Towards Rigorous Understanding of Neural Networks via
  Semantics-preserving Transformations
Towards Rigorous Understanding of Neural Networks via Semantics-preserving Transformations
Maximilian Schlüter
Gerrit Nolte
Alnis Murtovi
Bernhard Steffen
29
6
0
19 Jan 2023
Lower and Upper Bounds for Numbers of Linear Regions of Graph
  Convolutional Networks
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks
Hao Chen
Yu Wang
Huan Xiong
GNN
16
6
0
01 Jun 2022
1