Universality for Langevin-like spin glass dynamics
DOI10.1214/21-AAP1665zbMath1484.60108arXiv1911.08001OpenAlexW4205369694MaRDI QIDQ2075332
Eyal Lubetzky, Amir Dembo, Ofer Zeitouni
Publication date: 14 February 2022
Published in: The Annals of Applied Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1911.08001
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Large deviations (60F10) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31) Dynamics of disordered systems (random Ising systems, etc.) in time-dependent statistical mechanics (82C44)
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Cites Work
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- A generalization of the Lindeberg principle
- The eigenvalues of random symmetric matrices
- Symmetric Langevin spin glass dynamics
- Averaged and quenched propagation of chaos for spin glass dynamics
- Large deviations and mean-field theory for asymmetric random recurrent neural networks
- The thermodynamic limit in mean field spin glass models
- Large deviations for Langevin spin glass dynamics
- Sanov results for Glauber spin-glass dynamics
- Large deviations, dynamics and phase transitions in large stochastic and disordered neural networks
- Universality in Sherrington-Kirkpatrick's spin glass model
- An Introduction to Random Matrices
- Gaussian averages, Bernoulli averages, and Gibbs' measures
- Large deviations for randomly connected neural networks: I. Spatially extended systems
- Large deviations for randomly connected neural networks: II. State-dependent interactions
- Neural networks and physical systems with emergent collective computational abilities.
