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Abstraction Mechanisms Predict Generalization in Deep Neural Networks

Abstraction Mechanisms Predict Generalization in Deep Neural Networks

27 May 2019
Alex Gain
H. Siegelmann
    AI4CE
ArXivPDFHTML

Papers citing "Abstraction Mechanisms Predict Generalization in Deep Neural Networks"

5 / 5 papers shown
Title
Understanding Activation Patterns in Artificial Neural Networks by
  Exploring Stochastic Processes
Understanding Activation Patterns in Artificial Neural Networks by Exploring Stochastic Processes
S. Lehmler
Muhammad Saif-ur-Rehman
Tobias Glasmachers
Ioannis Iossifidis
19
0
0
01 Aug 2023
Deep neural networks architectures from the perspective of manifold
  learning
Deep neural networks architectures from the perspective of manifold learning
German Magai
AAML
AI4CE
16
6
0
06 Jun 2023
FACT: Learning Governing Abstractions Behind Integer Sequences
FACT: Learning Governing Abstractions Behind Integer Sequences
Peter Belcak
Ard Kastrati
Flavio Schenker
Roger Wattenhofer
31
5
0
20 Sep 2022
Topology and geometry of data manifold in deep learning
Topology and geometry of data manifold in deep learning
German Magai
A. Ayzenberg
AAML
19
11
0
19 Apr 2022
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
177
1,185
0
30 Nov 2014
1