Cédric Gerbelot

Engineering · Physical Sciences

10h-index221citations30works2.22yr avg
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Research Topics

Sparse and Compressive Sensing Techniques(10), Neural Networks and Applications(8), Stochastic Gradient Optimization Techniques(8), Statistical Methods and Inference(7), Markov Chains and Monte Carlo Methods(4)

Publications30 total

Asymptotics of Non-Convex Generalized Linear Models in High-Dimensions: A proof of the replica formula
arXiv (Cornell University)·2025Open Access
Permutation recovery of spikes in noisy high-dimensional tensor estimation
arXiv (Cornell University)·2024Open Access
Applying statistical learning theory to deep learning
Journal of Statistical Mechanics Theory and Experiment·2024· 2 cited
Stochastic gradient descent in high dimensions for multi-spiked tensor PCA
arXiv (Cornell University)·2024Open Access
Langevin dynamics for high-dimensional optimization: the case of multi-spiked tensor PCA
arXiv (Cornell University)·2024Open Access
Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods
SIAM Journal on Mathematics of Data Science·2024· 11 citedOpen Access
Applying statistical learning theory to deep learning
arXiv (Cornell University)·2023Open Access
Fluctuations, bias, variance and ensemble of learners: exact asymptotics for convex losses in high-dimension <sup>*</sup>
Journal of Statistical Mechanics Theory and Experiment·2023· 1 citedOpen Access
Multi-layer state evolution under random convolutional design <sup>*</sup>
Journal of Statistical Mechanics Theory and Experiment·2023Open Access
Ballistic Brownian Motion of Nanoconfined DNA
ACS Nano·2023· 10 citedOpen Access
Graph-based approximate message passing iterations
Information and Inference A Journal of the IMA·2023· 21 citedOpen Access
Ballistic Brownian motion of nanoconfined DNA
2023Open Access
Learning curves for the multi-class teacher–student perceptron
Machine Learning Science and Technology·2023· 16 citedOpen Access
Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima’s Replica Formula)
IEEE Transactions on Information Theory·2022· 28 citedOpen Access
Learning curves of generic features maps for realistic datasets with a teacher-student model*
Journal of Statistical Mechanics Theory and Experiment·2022· 57 citedOpen Access
Rigorous dynamical mean field theory for stochastic gradient descent methods
arXiv (Cornell University)·2022· 6 citedOpen Access
Statistical learning in high dimensions : a rigorous statistical physics approach
theses.fr (ABES)·2022Open Access
Multi-layer State Evolution Under Random Convolutional Design
arXiv (Cornell University)·2022Open Access
Learning curves for the multi-class teacher-student perceptron
arXiv (Cornell University)·2022· 2 citedOpen Access
Fluctuations, Bias, Variance &amp; Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension
arXiv (Cornell University)·2022Open Access
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Frequent Co-authors

Florent Krząkała(16), Lenka Zdeborová(11), Bruno Loureiro(9), Alia Abbara(4), Francesca Mignacco(4), Gabriele Sicuro(4), Hugo Cui(3), Sebastian Goldt(3), Marc Mézard(3), Ignacio Madrid(3), Akira Fujiwara(3), Shuo Li(3), Simon Grall(3), Katsuhiko Nishiguchi(3), Arnaud Chovin(3), Christophe Demaille(3), Nicolas Clément(3), Gérard Ben Arous(3), Vanessa Piccolo(3), Raphaël Berthier(2)