Publications

Antoine Maillard, Afonso S Bandeira, David Belius, Ivan Dokmanić, Shuta Nakajima (2023). Injectivity of ReLU networks: perspectives from statistical physics. arXiv preprint arXiv:2302.14112.

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Jonathan Dong, Lorenzo Valzania, Antoine Maillard, Thanh-an Pham, Sylvain Gigan, Michael Unser (2023). Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial. IEEE Signal Processing Magazine.

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Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová (2022). Optimal denoising of rotationally invariant rectangular matrices. Mathematical and Scientific Machine Learning.

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Afonso S Bandeira, Antoine Maillard, Richard Nickl, Sven Wang (2022). On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions. arXiv preprint arXiv:2209.02001.

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Antoine Maillard, Florent Krzakala, Marc Mézard, Lenka Zdeborová (2022). Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising. Journal of Statistical Mechanics: Theory and Experiment.

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Afonso S Bandeira, Antoine Maillard, Nikita Zhivotovskiy (2022). A remark on Kashin’s discrepancy argument and partial coloring in the Komlós conjecture. Portugaliae Mathematica.

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Antoine Maillard, Florent Krzakala, Yue M Lu, Lenka Zdeborová (2022). Construction of optimal spectral methods in phase retrieval. Mathematical and Scientific Machine Learning.

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Antoine Maillard (2021). Fundamental limits of high-dimensional estimation. PhD Thesis.

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Antoine Maillard (2021). Large deviations of extreme eigenvalues of generalized sample covariance matrices. EPL (Europhysics Letters).

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Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová (2020). Phase retrieval in high dimensions: Statistical and computational phase transitions. NeurIPS 2020.

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Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová (2020). The spiked matrix model with generative priors. IEEE Transactions on Information Theory.

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Antoine Maillard, Gérard Ben Arous, Giulio Biroli (2020). Landscape complexity for the empirical risk of generalized linear models. Mathematical and Scientific Machine Learning.

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Antoine Maillard, Laura Foini, Alejandro Lage Castellanos, Florent Krzakala, Marc Mézard, Lenka Zdeborová (2019). High-temperature expansions and message passing algorithms. Journal of Statistical Mechanics: Theory and Experiment.

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Corentin Bertrand, Olivier Parcollet, Antoine Maillard, Xavier Waintal (2019). Quantum Monte Carlo algorithm for out-of-equilibrium Green's functions at long times. Physical Review B.

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Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová (2019). The committee machine: computational to statistical gaps in learning a two-layers neural network. Journal of Statistical Mechanics: Theory and Experiment.

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M Schenk, X Buffat, K Li, A Maillard (2018). Vlasov description of the effects of nonlinear chromaticity on transverse coherent beam instabilities. Physical Review Accelerators and Beams.

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Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala (2018). The mutual information in random linear estimation beyond iid matrices. 2018 IEEE International Symposium on Information Theory (ISIT).

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Michael Schenk, Xavier Buffat, Lee Carver, Kevin Li, Antoine Maillard, Elias Métral (2018). Experiments and Theory on Beam Stabilization with Second-Order Chromaticity. 61st ICFA ABDW on High-Intensity and High-Brightness Hadron Beams (HB'18), Daejeon, Korea, 17-22 June 2018.

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Stephen R Green, Antoine Maillard, Luis Lehner, Steven L Liebling (2015). Islands of stability and recurrence times in AdS. Physical Review D.

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