Florent Krzakala

Q: What Schools Are Affiliated With Florent Krzakala

Florent Krzakala is affiliated with the following schools: Sorbonne University, Paris Sciences et Lettres University, Université Paris Cité, École Polytechnique Fédérale de Lausanne, University of Warsaw

Florent Krzakala's AcademicInfluence.com Rankings

Florent Krzakala

Physics

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#8884

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Physics

Florent Krzakala's Degrees

Masters Physics Université Paris Cité
Bachelors Physics Université Paris Cité

Why Is Florent Krzakala Influential?

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According to Wikipedia, Florent Krzakala is a French physicist and applied mathematician, currently a professor at EPFL . His research focuses on the resolution of theoretical problems in physics, computer science, machine learning, statistics and signal processing using mathematical tools inspired by the field of statistical physics.

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Florent Krzakala's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications (2011) (708)
Spectral redemption in clustering sparse networks (2013) (581)
Gibbs states and the set of solutions of random constraint satisfaction problems (2006) (425)
Statistical physics of inference: thresholds and algorithms (2015) (314)
Statistical physics-based reconstruction in compressed sensing (2011) (282)
Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices (2012) (256)
Phase Transitions in the Coloring of Random Graphs (2007) (209)
Reference-less measurement of the transmission matrix of a highly scattering material using a DMD and phase retrieval techniques. (2015) (171)
Optimal errors and phase transitions in high-dimensional generalized linear models (2017) (163)
Phase transition in the detection of modules in sparse networks (2011) (161)
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula (2016) (150)
Entropy and mutual information in models of deep neural networks (2018) (137)
Spectral Clustering of graphs with the Bethe Hessian (2014) (135)
Adaptive damping and mean removal for the generalized approximate message passing algorithm (2014) (123)
Model selection for degree-corrected block models (2012) (114)
Jamming versus glass transitions. (2008) (112)
A Landscape Analysis of Constraint Satisfaction Problems (2007) (108)
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime (2020) (102)
Hiding Quiet Solutions in Random Constraint Satisfaction Problems (2009) (102)
The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective (2012) (101)
Information-theoretic thresholds from the cavity method (2016) (96)
Statistical and computational phase transitions in spiked tensor estimation (2017) (95)
Generalisation error in learning with random features and the hidden manifold model (2020) (93)
Energy gaps in quantum first-order mean-field–like transitions: The problems that quantum annealing cannot solve (2009) (92)
On convergence of approximate message passing (2014) (91)
MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel (2015) (89)
Random projections through multiple optical scattering: Approximating Kernels at the speed of light (2015) (87)
Simple glass models and their quantum annealing. (2008) (86)
Spin and link overlaps in three-dimensional spin glasses. (2000) (85)
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher–student setup (2019) (85)
Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications (2017) (84)
The mutual information in random linear estimation (2016) (83)
Phase Transitions and Sample Complexity in Bayes-Optimal Matrix Factorization (2014) (81)
Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes (2015) (80)
Energy exponents and corrections to scaling in Ising spin glasses (2002) (75)
Phase transitions in sparse PCA (2015) (73)
Mutual information in rank-one matrix estimation (2016) (71)
The committee machine: computational to statistical gaps in learning a two-layers neural network (2018) (69)
Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction (2020) (69)
First-order transitions and the performance of quantum algorithms in random optimization problems (2010) (66)
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation (2017) (65)
Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs (2004) (60)
Generalization of the cavity method for adiabatic evolution of Gibbs states (2010) (55)
Inference in particle tracking experiments by passing messages between images (2009) (55)
Path-integral representation for quantum spin models: Application to the quantum cavity method and Monte Carlo simulations (2008) (55)
Variational free energies for compressed sensing (2014) (54)
Modelling the influence of data structure on learning in neural networks (2019) (54)
The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices (2018) (53)
Spectral detection in the censored block model (2015) (52)
The role of regularization in classification of high-dimensional noisy Gaussian mixture (2020) (52)
Behavior of Ising spin glasses in a magnetic field. (2007) (52)
Elusive spin-glass phase in the random field Ising model. (2009) (51)
Learning curves of generic features maps for realistic datasets with a teacher-student model (2021) (51)
Spectral detection on sparse hypergraphs (2015) (51)
Following Gibbs states adiabatically —The energy landscape of mean-field glassy systems (2009) (51)
Swept Approximate Message Passing for Sparse Estimation (2015) (50)
Approximate message-passing with spatially coupled structured operators, with applications to compressed sensing and sparse superposition codes (2013) (50)
Optical Reservoir Computing Using Multiple Light Scattering for Chaotic Systems Prediction (2019) (48)
Temperature and disorder chaos in three-dimensional Ising spin glasses. (2006) (47)
Multi-layer generalized linear estimation (2017) (47)
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy (2015) (46)
Potts glass on random graphs (2007) (43)
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed (2021) (40)
Estimation in the Spiked Wigner Model: A Short Proof of the Replica Formula (2018) (40)
Replica analysis and approximate message passing decoder for superposition codes (2014) (39)
The hard-core model on random graphs revisited (2013) (39)
Critical ageing of Ising ferromagnets relaxing from an ordered state (2006) (37)
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models (2019) (37)
The Spiked Matrix Model With Generative Priors (2019) (37)
Sparse Estimation with the Swept Approximated Message-Passing Algorithm (2014) (36)
Approximate message passing with restricted Boltzmann machine priors (2015) (36)
The secondary structure of RNA under tension (2002) (35)
Phase recovery from a Bayesian point of view: The variational approach (2014) (35)
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures (2020) (35)
The Gaussian equivalence of generative models for learning with shallow neural networks (2020) (34)
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model (2019) (33)
Phase diagram and approximate message passing for blind calibration and dictionary learning (2013) (32)
Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models (2017) (32)
Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference (2018) (32)
Fragility and hysteretic creep in frictional granular jamming. (2009) (31)
Performance of simulated annealing in p-spin glasses (2013) (31)
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines (2017) (31)
Spin glass models with ferromagnetically biased couplings on the Bethe lattice: analytic solutions and numerical simulations (2004) (30)
Quiet Planting in the Locked Constraint Satisfaction Problems (2009) (30)
Comparative study for inference of hidden classes in stochastic block models (2012) (30)
Nature of the glassy phase of RNA secondary structure (2001) (29)
Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model (2021) (29)
Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering (2016) (28)
The Gaussian equivalence of generative models for learning with two-layer neural networks (2020) (28)
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification (2020) (28)
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization (2020) (27)
Lattice model for colloidal gels and glasses. (2008) (27)
Belief-propagation reconstruction for discrete tomography (2012) (27)
On melting dynamics and the glass transition. II. Glassy dynamics as a melting process. (2011) (26)
Principled Training of Neural Networks with Direct Feedback Alignment (2019) (26)
Chaotic temperature dependence in a model of spin glasses (2002) (26)
Fundamental limits of detection in the spiked Wigner model (2018) (25)
Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima’s Replica Formula) (2020) (25)
Exact asymptotics for phase retrieval and compressed sensing with random generative priors (2019) (24)
Generalization error rates in kernel regression: the crossover from the noiseless to noisy regime (2021) (24)
On melting dynamics and the glass transition. I. Glassy aspects of melting dynamics. (2011) (24)
Non-equilibrium critical dynamics of the ferromagnetic Ising model with Kawasaki dynamics (2004) (23)
High-temperature expansions and message passing algorithms (2019) (23)
Zero-temperature responses of a 3D spin glass in a magnetic field. (2001) (22)
Disorder chaos in spin glasses (2005) (21)
No spin glass phase in the ferromagnetic random-field random-temperature scalar Ginzburg–Landau model (2010) (21)
Blind Calibration in Compressed Sensing using Message Passing Algorithms (2013) (21)
Finite Size Corrections and Likelihood Ratio Fluctuations in the Spiked Wigner Model (2017) (21)
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach (2015) (20)
Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstruction (2012) (20)
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions (2021) (20)
Phase retrieval in high dimensions: Statistical and computational phase transitions (2020) (20)
Spectral density of the non-backtracking operator on random graphs (2014) (20)
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines (2016) (19)
Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units (2019) (19)
Scaling Up Echo-State Networks With Multiple Light Scattering (2016) (19)
Approximate survey propagation for statistical inference (2018) (18)
Large-scale low-energy excitations in 3-d spin glasses (2000) (18)
Reweighted Belief Propagation and Quiet Planting for Random K-SAT (2012) (17)
Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems (2007) (17)
Performance Limits for Noisy Multimeasurement Vector Problems (2016) (17)
Statistical Physics, Optimization, Inference, and Message-Passing Algorithms: Lecture Notes of the Les Houches School of Physics: Special Issue, October 2013 (2015) (17)
Decoding from pooled data: Phase transitions of message passing (2017) (16)
Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method (2018) (16)
Asymptotic errors for convex penalized linear regression beyond Gaussian matrices. (2020) (16)
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval (2020) (15)
Glassy properties of the Kawasaki dynamics of two-dimensional ferromagnets. (2004) (15)
Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passing (2013) (15)
Quantum Annealing of Hard Problems (2009) (15)
Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices. (2020) (15)
Approximate message-passing for convex optimization with non-separable penalties (2018) (13)
Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing (2017) (13)
Epidemic mitigation by statistical inference from contact tracing data (2020) (13)
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation (2015) (13)
Following states in temperature in the spherical s + p-spin glass model (2012) (12)
Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising (2021) (12)
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension (2022) (12)
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension (2022) (12)
Non-adaptive pooling strategies for detection of rare faulty items (2013) (12)
Chaos in spin glasses (2007) (11)
Clustering from sparse pairwise measurements (2016) (11)
Decoding from Pooled Data: Sharp Information-Theoretic Bounds (2016) (11)
Robust phase retrieval with the swept approximate message passing (prSAMP) algorithm (2016) (11)
The nature of the different zero-temperature phases in discrete two-dimensional spin glasses: entropy, universality, chaos and cascades in the renormalization group flow (2011) (11)
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks (2022) (10)
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning (2019) (10)
On the relation between kinetically constrained models of glass dynamics and the random first-order transition theory (2012) (10)
Compressed sensing and Approximate Message Passing with spatially-coupled Fourier and Hadamard matrices (2013) (9)
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment (2020) (9)
On temperature chaos in Ising and XY spin glasses (2003) (9)
Reservoir Computing meets Recurrent Kernels and Structured Transforms (2020) (9)
Generalisation dynamics of online learning in over-parameterised neural networks (2019) (9)
Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients (2021) (8)
Random-field p-spin-glass model on regular random graphs (2011) (8)
Aging, memory and rejuvenation: some lessons from simple models (2005) (8)
Absence of an equilibrium ferromagnetic spin-glass phase in three dimensions. (2002) (8)
Ultrametric probe of the spin-glass state in a field (2012) (7)
Discrete energy landscapes and replica symmetry breaking at zero temperature (2000) (7)
Construction of optimal spectral methods in phase retrieval (2020) (6)
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks (2020) (6)
Fast Phase Retrieval for High Dimensions: A Block-Based Approach (2016) (6)
First-order transitions for random optimization problems in a transverse field (2009) (6)
Scampi: a robust approximate message-passing framework for compressive imaging (2015) (5)
On the universality of noiseless linear estimation with respect to the measurement matrix (2019) (5)
Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media (2018) (5)
Fast Randomized Semi-Supervised Clustering (2016) (5)
Belief-propagation-guided Monte-Carlo sampling (2013) (5)
Constraint optimisation and landscapes (2007) (5)
Robust error correction for real-valued signals via message-passing decoding and spatial coupling (2013) (5)
Rigorous dynamical mean field theory for stochastic gradient descent methods (2022) (4)
Comment on "Ultrametricity in the Edwards-Anderson model". (2007) (4)
Local excitations in mean-field spin glasses (2003) (4)
Spectral bounds for the Ising ferromagnet on an arbitrary given graph (2016) (4)
LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor (2021) (4)
TRAMP: Compositional Inference with TRee Approximate Message Passing (2020) (4)
Constraint optimization and landscapes (2007) (4)
Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model (2019) (3)
Decoding From Pooled Data: Phase Transitions of Message Passing (2017) (3)
Optimal denoising of rotationally invariant rectangular matrices (2022) (3)
How many colors to color a random graph? Cavity, complexity, stability and all that (2004) (3)
A study of uncertainty quantification in overparametrized high-dimensional models (2022) (3)
Low-rank Matrix Estimation with Inhomogeneous Noise (2022) (3)
Trivial link but non-trivial spin overlaps in 3-dimensional spin glasses (2000) (3)
Theoretical characterization of uncertainty in high-dimensional linear classification (2022) (3)
Statistical physics, optimization, inference and message-passing algorithms : École de Physique des Houches special issue, 30 September-11 October 2013 (2016) (3)
41 44 v 3 [ qu an tph ] 24 S ep 2 00 8 Simple Glass Models and Their Quantum Annealing (2008) (2)
Error Rates for Kernel Classification under Source and Capacity Conditions (2022) (2)
THE GENERALIZED APPROXIMATE MESSAGE PASSING ALGORITHM (2015) (2)
Intensity-only optical compressive imaging using a multiply scattering material : a double phase retrieval system (2015) (2)
Precise asymptotics for phase retrieval and compressed sensing with random generative priors (2019) (2)
Universality laws for Gaussian mixtures in generalized linear models (2023) (2)
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks (2023) (2)
Statistical Physics of Inference problems (2014) (2)
Glassy aspects of melting dynamics, Part 1 (2010) (1)
Zero Temperature Phase Diagram of Finite Connectivity Spin Glasses (2004) (1)
Optical reservoir computing for high-dimensional spatio-temporal chaotic systems prediction (Conference Presentation) (2020) (1)
Bayesian reconstruction of memories stored in neural networks from their connectivity (2021) (1)
Following Gibbs States -- The Energy Landscape of Mean Field Glassy Systems (2009) (1)
Secure Coding via Gaussian Random Fields (2022) (1)
Belief Propagation for the ( physicist ) layman (2011) (1)
Artificial intelligence: From electronics to optics (2020) (1)
Hiking through glassy phases: physics beyond aging (2002) (1)
Gaussian Universality of Perceptrons with Random Labels (2022) (1)
Glassy aspects of melting dynamics (On melting dynamics and the glass transition, Part I) (2010) (1)
Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation (2023) (1)
Blind calibration for compressed sensing: state evolution and an online algorithm (2019) (1)
Tree-AMP: Compositional Inference with Tree Approximate Message Passing (2020) (1)
Optimal Learning of Deep Random Networks of Extensive-width (2023) (1)
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning (2022) (1)
Approximate Message Passing with Restricted (2015) (0)
Supplementary Material for “Entropy and mutual information in models of deep neural networks” (2019) (0)
O ct 2 00 8 A Lattice Model for Colloidal Gels and Glasses (2008) (0)
DETECTION LIMITS IN THE SPIKED WIGNER MODEL By (2019) (0)
2 5 O ct 2 00 1 Zero-temperature responses of a 3 D spin glass in a field (2022) (0)
Multi-layer State Evolution Under Random Convolutional Design (2022) (0)
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification – supplementary material (2021) (0)
O ct 2 00 8 On the path integral representation for quantum spin models and its application to the quantum cavity method and to Monte Carlo simulations (2008) (0)
Statistical Physics of Inference and Bayesian Estimation (2015) (0)
Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery (2023) (0)
Deep seq2seq architecture for DNA sequence decoding from noisy data (2019) (0)
1 Introduction While the traditional approach to learning and generalization follows the Vapnik-Chervonenkis [ 1 ] and (2019) (0)
O ct 2 00 3 Energy exponents and corrections to scaling in Ising spin glasses (2007) (0)
On double-descent in uncertainty quantification in overparametrized models (2022) (0)
On the ordering of Ising spin glasses in a field (2007) (0)
Glassy dynamics as a melting process, Part 2 (2010) (0)
Statistical mechanics of the maximum-average submatrix problem (2023) (0)
Quantum energy gaps and first-order mean-field-like transitions (2009) (0)
Optimal Algorithms for the Inhomogeneous Spiked Wigner Model (2023) (0)
Expectation consistency for calibration of neural networks (2023) (0)
41 44 v 1 [ qu an tph ] 25 J un 2 00 8 Simple Glass Models and their Quantum Annealing (2008) (0)
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16) (2016) (0)
Blind Calibration for Sparse Regression: A State Evolution Analysis (2019) (0)
Theoretical Limits of Streaming Inference and Mini-Batch Message-Passing Algorithms (2017) (0)
Quantum Annealing of Hard Problems(Frontiers in Nonequilibrium Physics-Fundamental Theory, Glassy & Granular Materials, and Computational Physics-) (2010) (0)
Glassy dynamics as a melting process (On melting dynamics and the glass transition, Part II) (2010) (0)
Quantum energy gaps and first-order mean-field transitions (2009) (0)
Subspace clustering in high-dimensions: Phase transitions \& Statistical-to-Computational gap (2022) (0)
Ultrametricity in the Edwards-Anderson model : Reply to a comment by T. Jörg and F. Krzakala (2008) (0)

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What Schools Are Affiliated With Florent Krzakala?

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Florent Krzakala's Academic­Influence.com Rankings