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Computer Science

D-Index
56
Citations
12008
World Ranking
4091
National Ranking
92

Overview

Florent Krzakala is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research contributions focus primarily within the field of Computer Science, with a strong emphasis on Artificial Intelligence and associated subfields.

Their main areas of study include:

  • Artificial Intelligence
  • Statistics and Probability
  • Computational Mechanics
  • Statistical and Nonlinear Physics
  • Signal Processing

Key topics explored in their work encompass:

  • Neural Networks and Applications
  • Sparse and Compressive Sensing Techniques
  • Statistical Methods and Inference
  • Gaussian Processes and Bayesian Inference
  • Stochastic Gradient Optimization Techniques
  • Blind Source Separation Techniques
  • Statistical Mechanics and Entropy

Florent Krzakala has authored numerous academic papers, with notable examples including:

  • "Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction," 2020, Physical Review X
  • "Generalisation error in learning with random features and the hidden manifold model*," 2021, Journal of Statistical Mechanics Theory and Experiment
  • "Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime," 2020, arXiv (Cornell University)
  • "Learning curves of generic features maps for realistic datasets with a teacher-student model*," 2022, Journal of Statistical Mechanics Theory and Experiment

These papers span research on learning models, statistical mechanics, and system prediction within computational and theoretical frameworks.

Frequent co-authors collaborating with Florent Krzakala include:

  • Lenka Zdeborová
  • Bruno Loureiro
  • Hugo Cui
  • Cédric Gerbelot
  • Ludovic Stephan

The majority of their publications appear in:

  • arXiv (Cornell University)
  • Journal of Statistical Mechanics Theory and Experiment
  • IEEE Transactions on Information Theory
  • Proceedings of the National Academy of Sciences
  • HAL (Le Centre pour la Communication Scientifique Directe)

Florent Krzakala's research encompasses a blend of theoretical and applied methods across artificial intelligence, statistical physics, and computational sciences. Their publication record demonstrates a continued engagement with topics that bridge statistical inference techniques and neural network applications, offering insights within a computational mechanics context.

Best Publications

  • Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications.

    Aurelien Decelle;Florent Krzakala;Cristopher Moore;Lenka Zdeborová

  • Spectral redemption in clustering sparse networks

    Florent Krzakala;Cristopher Moore;Elchanan Mossel;Joseph Neeman

  • Gibbs states and the set of solutions of random constraint satisfaction problems

    Florent Krzakała;Andrea Montanari;Federico Ricci-Tersenghi;Guilhem Semerjian

  • Statistical physics of inference: thresholds and algorithms

    Lenka Zdeborová;Florent Krzakala

  • Inference and phase transitions in the detection of modules in sparse networks.

    Aurelien Decelle;Florent Krzakala;Cristopher Moore;Lenka Zdeborová

  • Statistical-Physics-Based Reconstruction in Compressed Sensing

    Florent Krzakala;Marc Mézard;François Sausset;Yifan Sun;Yifan Sun

  • Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices

    Florent Krzakala;Marc Mézard;Francois Sausset;Yifan Sun;Yifan Sun

  • Phase transitions in the coloring of random graphs

    Lenka Zdeborová;Florent Krzakala

  • Reference-less measurement of the transmission matrix of a highly scattering material using a DMD and phase retrieval techniques

    Angélique Drémeau;Antoine Liutkus;David Martina;Ori Katz

  • Optimal errors and phase transitions in high-dimensional generalized linear models

    Jean Barbier;Florent Krzakala;Nicolas Macris;Léo Miolane

  • The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective

    Victor Bapst;Laura Foini;Florent Krzakala;Guilhem Semerjian

  • Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula

    jean barbier;Mohamad Dia;Nicolas Macris;Florent Krzakala

  • Landscape analysis of constraint satisfaction problems.

    Florent Krzakala;Jorge Kurchan

  • Adaptive damping and mean removal for the generalized approximate message passing algorithm

    Jeremy Vila;Philip Schniter;Sundeep Rangan;Florent Krzakala

  • Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction

    Mushegh Rafayelyan;Jonathan Dong;Yongqi Tan;Florent Krzakala

  • Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications

    Thibault Lesieur;Florent Krzakala;Florent Krzakala;Lenka Zdeborová

  • Entropy and mutual information in models of deep neural networks

    Marylou Gabrié;Andre Manoel;Clément Luneau;Jean Barbier

  • Hiding Quiet Solutions in Random Constraint Satisfaction Problems

    Florent Krzakala;Florent Krzakala;Lenka Zdeborová

  • Spectral Clustering of graphs with the Bethe Hessian

    Alaa Saade;Florent Krzakala;Lenka Zdeborova

  • Statistical and computational phase transitions in spiked tensor estimation

    Thibault Lesieur;Leo Miolane;Marc Lelarge;Florent Krzakala

  • Random projections through multiple optical scattering: Approximating Kernels at the speed of light

    A. Saade;F. Caltagirone;I. Carron;L. Daudet

  • Modelling the influence of data structure on learning in neural networks: the hidden manifold model

    Sebastian Goldt;Marc Mézard;Florent Krzakala;Lenka Zdeborová

Frequent Co-Authors

Lenka Zdeborová
Lenka Zdeborová École Polytechnique Fédérale de Lausanne
Laurent Daudet
Laurent Daudet Université Paris Cité
Marc Lelarge
Marc Lelarge École Normale Supérieure
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Yue M. Lu
Yue M. Lu Beijing University of Posts and Telecommunications
Cristopher Moore
Cristopher Moore Santa Fe Institute
Giorgio Parisi
Giorgio Parisi Sapienza University of Rome
Pasquale Calabrese
Pasquale Calabrese International School for Advanced Studies
Philip Schniter
Philip Schniter The Ohio State University
Sundeep Rangan
Sundeep Rangan New York University

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