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Critical percolation as a framework to analyze the training of deep networks
Zohar Ringel
, Rodrigo De Bem
Racah Institute of Physics
Research output
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Contribution to conference
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Paper
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peer-review
1
Scopus citations
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Keyphrases
Classification Task
33%
CNN Architecture
33%
Cost Function
100%
Critical Percolation
100%
Data Topology
33%
Deep Learning
33%
Deep Network
100%
Euclidean Space
33%
Experiment Analysis
33%
Global Minimum
33%
Learning Algorithm
33%
Local Minima
33%
Numerical Analysis
33%
Obstacles to Learning
33%
Planar Graph
33%
Reachability
33%
Structured Input
33%
Topological Classification
33%
Training Experiment
33%
Computer Science
Classification Task
100%
Convolutional Neural Network
100%
Deep Learning Method
100%
Learning Algorithm
100%
Local Minimum
100%
Planar Graph
100%
Mathematics
Convolutional Neural Network
33%
Cost Function
100%
Deep Learning Method
33%
Euclidean Space
33%
Input Data
33%
Local Minimum
33%
Numerical Analysis
33%
Planar Graph
33%
Rare Event
33%
Biochemistry, Genetics and Molecular Biology
Solution and Solubility
100%