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Recent years witnessed the development of powerful generative models based on flows, diffusion or autoregressive neural networks, achieving remarkable success in generating data from examples with applications in a broad range of areas.
The fluctuation-dissipation theorem
Rep Kubo · 1966
Earlier work this paper cites.
Solution of’solvable model of a spin glass’
David J Thouless, Philip W Anderson, and Robert G Palmer · 1977
Earlier work this paper cites.
Infinite number of order parameters for spin-glasses
G Parisi · 1979
Earlier work this paper cites.
Random-energy model: Limit of a family of disordered models
Bernard Derrida · 1980
Earlier work this paper cites.
Estimation of the mean of a multivariate normal distribution
Charles M Stein · 1981
Earlier work this paper cites.
Reverse-time diffusion equation models
Brian DO Anderson · 1982
Earlier work this paper cites.
The simplest spin glass
David J Gross and Marc Mézard · 1984
Earlier work this paper cites.
Spin glass theory and beyond: An Introduction to the Replica Method and Its Applications
Marc Mézard, Giorgio Parisi, and Miguel Angel Virasoro · 1987
Earlier work this paper cites.
Dynamics of the structural glass transition and the p-spin—interaction spin-glass model
Theodore R Kirkpatrick and Devarajan Thirumalai · 1987
Earlier work this paper cites.
Connections between some kinetic and equilibrium theories of the glass transition
TR Kirkpatrick and PG Wolynes · 1987
Earlier work this paper cites.
Solving ordinary differential equations I: nonstiff problems (E. hairer, s. p. norsett, and g. wanner)
Roger Alexander · 1990
Earlier work this paper cites.
Entropy, relative entropy and mutual information
Thomas M Cover, Joy A Thomas, et al · 1991
Earlier work this paper cites.
The spherical p-spin interaction spin glass model: the statics
Andrea Crisanti and H-J Sommers · 1992
Earlier work this paper cites.
Analytical solution of the off-equilibrium dynamics of a long-range spin-glass model
Leticia F Cugliandolo and Jorge Kurchan · 1993
Earlier work this paper cites.
The spherical p-spin interaction spin-glass model: the dynamics
Andrea Crisanti, Heinz Horner, and H J Sommers · 1993
Earlier work this paper cites.
Out of equilibrium dynamics in spin-glasses and other glassy systems
Jean-Philippe Bouchaud, Leticia F Cugliandolo, Jorge Kurchan, and Marc Mézard · 1998
Earlier work this paper cites.
The nishimori line and bayesian statistics
Yukito Iba · 1999
Earlier work this paper cites.
Error-correcting codes and image restoration with multiple stages of dynamics
KY Michael Wong and Hidetoshi Nishimori · 2000
Earlier work this paper cites.
Statistical Physics of Spin Glasses and Information Processing: An Introduction
Hidetoshi Nishimori · 2001
Earlier work this paper cites.
Analytic and algorithmic solution of random satisfiability problems
Marc Mézard, Giorgio Parisi, and Riccardo Zecchina · 2002
Earlier work this paper cites.
Bicolouring random hypergraphs
Tommaso Castellani, Vincenzo Napolano, Federico Ricci-Tersenghi, and Riccardo Zecchina · 2003
Earlier work this paper cites.
Survey-propagation decimation through distributed local computations
Joel Chavas, Cyril Furtlehner, Marc Mézard, and Riccardo Zecchina · 2005
Earlier work this paper cites.
Mutual information and minimum mean-square error in gaussian channels
Dongning Guo, Shlomo Shamai, and Sergio Verdú · 2005
Earlier work this paper cites.
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
Jinho Baik, Gérard Ben Arous, and Sandrine Péché · 2005
Earlier work this paper cites.
Cugliandolo-kurchan equations for dynamics of spin-glasses
Gérard Ben Arous, Amir Dembo, and Alice Guionnet · 2006
Earlier work this paper cites.
Rigorous inequalities between length and time scales in glassy systems
Andrea Montanari and Guilhem Semerjian · 2006
Earlier work this paper cites.
Pattern recognition and machine learning
Christopher M Bishop and Nasser M Nasrabadi · 2006
Earlier work this paper cites.
Eigenvalues of large sample covariance matrices of spiked population models
Jinho Baik and Jack W Silverstein · 2006
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Reconstruction on trees and spin glass transition
Marc Mézard and Andrea Montanari · 2006
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Gibbs states and the set of solutions of random constraint satisfaction problems
Florent Krzakała, Andrea Montanari, Federico Ricci-Tersenghi, Guilhem Semerjian, and Lenka Zdeborová · 2007
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Solving constraint satisfaction problems through belief propagation-guided decimation
Andrea Montanari, Federico Ricci-Tersenghi, and Guilhem Semerjian · 2007
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Modern coding theory
Tom Richardson and Ruediger Urbanke · 2008
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Entropy landscape and non-gibbs solutions in constraint satisfaction problems
Luca Dall’Asta, Abolfazl Ramezanpour, and Riccardo Zecchina · 2008
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Thermodynamic signature of growing amorphous order in glass-forming liquids
GBJP Biroli, J-P Bouchaud, Andrea Cavagna, Tomás S Grigera, and Paolo Verrocchio · 2008
Earlier work this paper cites.
Transport equation and cauchy problem for non-smooth vector fields
Luigi Ambrosio, Luis Caffarelli, Michael G Crandall, Lawrence C Evans, Nicola Fusco, and Luigi Ambrosio · 2008
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Information, physics, and computation
Marc Mezard and Andrea Montanari · 2009
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Message-passing algorithms for compressed sensing
David L. Donoho, Arian Maleki, and Andrea Montanari · 2009
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On the cavity method for decimated random constraint satisfaction problems and the analysis of belief propagation guided decimation algorithms
Federico Ricci-Tersenghi and Guilhem Semerjian · 2009
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Exact solution of the gauge symmetric p-spin glass model on a complete graph
Satish Babu Korada and Nicolas Macris · 2009
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Hiding quiet solutions in random constraint satisfaction problems
Florent Krzakala and Lenka Zdeborová · 2009
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Optimal transport: old and new
Cédric Villani et al · 2009
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Generalization of the cavity method for adiabatic evolution of gibbs states
Lenka Zdeborová and Florent Krzakala · 2010
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The neural autoregressive distribution estimator
Hugo Larochelle and Iain Murray · 2011
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Theoretical perspective on the glass transition and amorphous materials
Ludovic Berthier and Giulio Biroli · 2011
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The dynamics of message passing on dense graphs, with applications to compressed sensing
Mohsen Bayati and Andrea Montanari · 2011
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On melting dynamics and the glass transition. i. glassy aspects of melting dynamics
Florent Krzakala and Lenka Zdeborová · 2011
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The Random First-Order Transition Theory of Glasses: A Critical Assessment
Giulio Biroli and Jean-Philippe Bouchaud · 2012
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Performance of a cavity-method-based algorithm for the prize-collecting steiner tree problem on graphs
Indaco Biazzo, Alfredo Braunstein, and Riccardo Zecchina · 2012
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The condensation transition in random hypergraph 2-coloring
Optimal errors and phase transitions in high-dimensional generalized linear models
Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, and Lenka Zdeborová · 2019
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Typology of phase transitions in bayesian inference problems
Federico Ricci-Tersenghi, Guilhem Semerjian, and Lenka Zdeborová · 2019
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Solving statistical mechanics using variational autoregressive networks
Dian Wu, Lei Wang, and Pan Zhang · 2019
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The adaptive interpolation method: a simple scheme to prove replica formulas in bayesian inference
Jean Barbier and Nicolas Macris · 2019
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Fundamental limits of symmetric low-rank matrix estimation
Marc Lelarge and Léo Miolane · 2019
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Biased landscapes for random constraint satisfaction problems
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Amin Coja-Oghlan and Lenka Zdeborová · 2012
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Iterative estimation of constrained rank-one matrices in noise
Sundeep Rangan and Alyson K Fletcher · 2012
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Generating sequences with recurrent neural networks
Alex Graves · 2013
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Thin shell implies spectral gap up to polylog via a stochastic localization scheme
Ronen Eldan · 2013
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Conditional random fields, planted constraint satisfaction and entropy concentration
Emmanuel Abbe and Andrea Montanari · 2013
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Random pinning glass transition: Hallmarks, mean-field theory and renormalization group analysis
Chiara Cammarota and Giulio Biroli · 2013
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The parisi ultrametricity conjecture
Dmitry Panchenko · 2013
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Denoising diffusion probabilistic models
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Score-based generative modeling through stochastic differential equations
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Equivariant flow-based sampling for lattice gauge theory
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Taming correlations through entropy-efficient measure decompositions with applications to mean-field approximation
Ronen Eldan · 2020
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Marvels and pitfalls of the langevin algorithm in noisy high-dimensional inference
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, and Lenka Zdeborová · 2020
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The estimation error of general first order methods
Michael Celentano, Andrea Montanari, and Yuchen Wu · 2020
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Complex dynamics in simple neural networks: Understanding gradient flow in phase retrieval
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, and Lenka Zdeborová · 2020
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Optimization and generalization of shallow neural networks with quadratic activation functions
Stefano Sarao Mannelli, Eric Vanden-Eijnden, and Lenka Zdeborová · 2020
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Statistical thresholds for tensor pca
Aukosh Jaganath, Patrick Lopatto, and Léo Miolane · 2020
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Geodiff: A geometric diffusion model for molecular conformation generation
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Efficient generative modeling of protein sequences using simple autoregressive models
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Overlap matrix concentration in optimal bayesian inference
Jean Barbier · 2021
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Estimation of low-rank matrices via approximate message passing
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On the computational tractability of statistical estimation on amenable graphs
Ahmed El Alaoui and Andrea Montanari · 2021
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An Invitation to Optimal Transport, Wasserstein Distances, and Gradient Flows
Alessio Figalli and Federico Glaudo · 2021
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Localization schemes: A framework for proving mixing bounds for markov chains
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Sampling from the sherrington-kirkpatrick gibbs measure via algorithmic stochastic localization
Ahmed El Alaoui, Andrea Montanari, and Mark Sellke · 2022
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An information-theoretic view of stochastic localization
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Disordered systems insights on computational hardness
David Gamarnik, Cristopher Moore, and Lenka Zdeborová · 2022
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The franz-parisi criterion and computational trade-offs in high dimensional statistics
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Stochastic interpolants: A unifying framework for flows and diffusions, 2023
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Github repository for sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective
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Machine-learning-assisted monte carlo fails at sampling computationally hard problems
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Limits and performances of algorithms based on simulated annealing in solving sparse hard inference problems
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Almost-linear planted cliques elude the metropolis process
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