dnner

Python library dnner - DNNs Entropy from Replicas. The code in this package computes the entropy, mutual information and MMSE of multi-layer GLMs given orthogonally-invariant matrices of arbitrary spectrum. More details available in arXiv:1805.09785 and our published NeurIPS 2018 paper

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References in zbMATH (referenced in 7 articles )

Showing results 1 to 7 of 7.
Sorted by year (citations)

  1. Benigni, Lucas; Péché, Sandrine: Eigenvalue distribution of some nonlinear models of random matrices (2021)
  2. Pandit, Parthe; Sahraee-Ardakan, Mojtaba; Rangan, Sundeep; Schniter, Philip; Fletcher, Alyson K.: Matrix inference and estimation in multi-layer models (2021)
  3. Barbier, Jean; Chan, Chun Lam; Macris, Nicolas: Concentration of multi-overlaps for random dilute ferromagnetic spin models (2020)
  4. Gribonval, Rémi; Blanchard, Gilles; Keriven, Nicolas; Traonmilin, Yann: Compressive statistical learning with random feature moments (2020)
  5. Merkh, Thomas; Montúfar, Guido: Factorized mutual information maximization. (2020)
  6. Barbier, Jean; Macris, Nicolas: The adaptive interpolation method: a simple scheme to prove replica formulas in Bayesian inference (2019)
  7. Gabrié, Marylou; Manoel, Andre; Luneau, Clément; Barbier, Jean; Macris, Nicolas; Krzakala, Florent; Zdeborová, Lenka: Entropy and mutual information in models of deep neural networks (2019)