Launch week offerEnds in00h00m00s

annual Promonthly Pro

Florent Krzakala

Has grant

Professor

Sorbonne Université

France

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in France Professors in Biostatistics Biostatistics professors in France

Recent Grants

Grant: Close

Phase diagrams and Algorithms for Inference and Learning – PAIL

Open Date: 2018-04-20

Close Date: 2021-10-19

Grant: Close

Phase diagrams and Algorithms for Inference and Learning

Open Date: 2018-04-01

Close Date: 2021-03-31

Grant: Close

Statistical Physics Approach to Reconstruction in Compressed Sensing

Open Date: 2012-10-01

Close Date: 2018-09-30

Grant: Close

Exploring the Limits of Computation from the Statistical Physics

Open Date: 2012-06-28

Close Date: 2017-03-31

Articles (20)

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (3)

Rodrigo Veiga

Assistant Professor

University of Nottingham

UNITED KINGDOM

View details

Nicolas Brunel

Professor

Bocconi University

ITALY

View details

Sebastian Goldt

Associate Professor

Scuola Internazionale Superiore di Studi Avanzati

ITALY

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Florent Krzakala

Research Interests

Make your next move.

Explore related searches

Recent Grants

Articles (20)

Sampling with flows, diffusion, and autoregressive neural networks from a spin-glass perspective

Gaussian universality of perceptrons with random labels

Bayesian reconstruction of memories stored in neural networks from their connectivity

Phase diagram of stochastic gradient descent in high-dimensional two-layer neural networks

Fluctuations, bias, variance and ensemble of learners: exact asymptotics for convex losses in high-dimension <sup>*</sup>

Multi-layer state evolution under random convolutional design <sup>*</sup>

Error scaling laws for kernel classification under source and capacity conditions

Message Passing and Its Applications

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

Analysis of learning a flow-based generative model from limited sample complexity

Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation

Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers

Bayesian Inference With Nonlinear Generative Models: Comments on Secure Learning

Compressed sensing with \(ℓ\)0-norm: statistical physics analysis & algorithms for signal recovery

Escaping mediocrity: how two-layer networks learn hard single-index models with SGD

Expectation consistency for calibration of neural networks

From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks

Learning Two-Layer Neural Networks, One (Giant) Step at a Time

Optimal Algorithms for the Inhomogeneous Spiked Wigner Model

Optimal Learning of Deep Random Networks of Extensive-width

Collaborators (3)

Rodrigo Veiga

Nicolas Brunel

Sebastian Goldt

Make your next move.