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Information Plane

To obtain the Information Plane (IP) of deep neural networks, which shows the trajectories of the hidden layers during training in a 2D plane using as coordinate axes the mutual information between the input and the hidden layer, and the mutual information between the output and the hidden layer.

Papers

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Showing 11–20 of 30 papers

TitleStatusHype
SoFaiR: Single Shot Fair Representation Learning—0
A Comparative Genomic Analysis of Coronavirus Families Using Chaos Game Representation and Fisher-Shannon Complexity—0
Distinguishing noise from chaos: objective versus subjective criteria using Horizontal Visibility Graph—0
Enhancing Neural Network Interpretability Through Conductance-Based Information Plane Analysis—0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane—0
Fundamental Limits and Tradeoffs in Invariant Representation Learning—0
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training—0
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels—0
Information Plane Analysis of Deep Neural Networks via Matrix--Based Renyi's Entropy and Tensor Kernels—0
Information Plane Analysis Visualization in Deep Learning via Transfer Entropy—0
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