Information flow in Deep Restricted Boltzmann Machines: An analysis of mutual information between inputs and outputs

Author:

Vera Matias,Rey Vega Leonardo,Piantanida Pablo

Funder

CONICET

Universidad de Buenos Aires

Horizon 2020

Secretaría de Ciencia y Técnica, Universidad de Buenos Aires

Horizon 2020 Framework Programme

H2020 Marie Skłodowska-Curie Actions

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

1. D. Kingma, M. Welling, Auto-encoding variational bayes, in: International Conference on Learning Representations (ICLR), 2013, pp. 1–14.

2. Mutual information neural estimation;Belghazi,2018

3. G. Pichler, P. Piantanida, G. Koliander, On the estimation of information measures of continuous distributions, https://arxiv.org/abs/2002.02851 (2020).

4. Learning representations for neural network-based classification using the information bottleneck principle;Amjad;IEEE Trans. Pattern Anal. Mach. Intell.,2020

5. P. Smolensky, Information processing in dynamical systems: Foundations of harmony theory, in: Parallel distributed processing: Explorations in the microstructure of cognition, MIT Press, 1986, pp. 194–281.

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