Random matrix theory

By Franz Wegner. 100 Years of Math Milestones, 2019

298 citations recorded by the source corpus.

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iNAP: An integrated network analysis pipeline for microbiome studies (2022, background): “Extended local similarity analysis (eLSA) [12] and liquid association (LA) [13] explore time ‐ dependent microbial associations for time series data.”
Free Probability and Random Matrices (2014, background): “For more on its diversity, beauty, and depth one should have a look at [6, 69, 171] or on the collection of survey articles on various aspects of random matrices in [2].”
The Random Matrix Theory of the Classical Compact Groups (2019, background): “standard Gaussian random variables and then returning Q from its internal QR-algorithm will not produce a Haar-distributed matrix; see [83] and [43] for further discussion.”
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning (2018, background): “7 Several overviews of RMT are available [143, 41, 71, 142, 22, 42, 110, 24].”
Supersymmetric SYK model and random matrix theory (2017, background): “These arguments might be made to be more general: supersymmetry could directly change the universal class of Hamiltonian (GOE/GUE/GSE) by classifying the symmetry class of supercharge, where combinations of Witten index and antiunitary operators will make some new antiunitaries; on the other hand, t”