Statistical mechanics of complex neural systems and high dimensional data
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Publication:3301560
DOI10.1088/1742-5468/2013/03/P03014zbMath1456.82801arXiv1301.7115OpenAlexW3102632574MaRDI QIDQ3301560
Madhu S. Advani, Surya Ganguli, Subhaneil Lahiri
Publication date: 11 August 2020
Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1301.7115
Neural biology (92C20) Neural nets applied to problems in time-dependent statistical mechanics (82C32)
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Cites Work
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- On the distribution of the roots of certain symmetric matrices
- Random projections of smooth manifolds
- A simple proof of the restricted isometry property for random matrices
- Level-spacing distributions and the Airy kernel
- Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.
- Nonintersecting Brownian excursions
- Statistical Mechanics of Learning
- Exact Distribution of the Maximal Height of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>p</mml:mi></mml:math>Vicious Walkers
- The Perceptron: A Model for Brain Functioning. I
- Extensions of Lipschitz mappings into a Hilbert space
- Random matrix theory
- Large deviations of the maximum eigenvalue in Wishart random matrices
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms
- Role of Homeostasis in Learning Sparse Representations
- Graphical Models, Exponential Families, and Variational Inference
- Information, Physics, and Computation
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- A Brownian-Motion Model for the Eigenvalues of a Random Matrix
- Learning a rule in a multilayer neural network
- Observation of a hexatic vortex glass in flux lattices of the high-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="italic">T</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant="italic">c</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>superconductor<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">Bi</mml:mi></mml:mrow><mml:mrow><mml:…
- Statistical Physics of Spin Glasses and Information Processing
- An elementary proof of a theorem of Johnson and Lindenstrauss
- Statistical mechanics of unsupervised structure recognition
- Compressed and Privacy-Sensitive Sparse Regression
- Survey propagation: An algorithm for satisfiability
- Neural networks and physical systems with emergent collective computational abilities.
- Sparse nonnegative solution of underdetermined linear equations by linear programming
- Neighborliness of randomly projected simplices in high dimensions
- Gibbs states and the set of solutions of random constraint satisfaction problems
- The space of interactions in neural network models
- Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ 1 minimization
- Statistical theory of superlattices
- An introduction to statistical modeling of extreme values
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