| Publications Adaptive Monte Carlo augmented with normalizing flows [pdf] Gabrié M., Rotskoff G. M., Vanden-Eijnden E. arXiv:2105.12603 (2021) More data or more parameters? Investigating the effect of data structure on generalization [pdf] d'Ascoli S., Gabrié M., Sagun L., Biroli G. arXiv:2103.05524 (2021) Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging [pdf] Lawrence H., Barmherzig D. A., Li H., Eickenberg M., Gabrié M. arXiv:2012.07386 (2020) - Accepted for publication at MSML 2021. Mean-field inference methods for neural networks, [pdf] Gabrié, M. Journal of Physics A: Mathematical and Theoretical, 53(22), 1–58. (2020) Blind calibration for compressed sensing: State evolution and an online algorithm, [pdf] Gabrié, M., Barbier, J., Krzakala, F., & Zdeborová, L. Journal of Physics A: Mathematical and Theoretical, 53(33), 334004. (2020) Entropy and mutual information in models of deep neural networks, [pdf] [spotlight short video] Gabrié, M., Manoel, A., Luneau, C., Barbier, J., Macris, N., Krzakala, F., & Zdeborová, L. Advances in Neural Information Processing Systems 31, 1826--1836 (2018) Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines, [pdf] Tramel, E. W., Gabrié, M., Manoel, A., Caltagirone, F., & Krzakala, F. Advances in Neural Physical Review X, 8(4), 041006. (2018) Phase transitions in the q-coloring of random hypergraphs, [pdf] Gabrié, M., Dani, V., Semerjian, G., & Zdeborová, L. Journal of Physics A: Mathematical and Theoretical, 50(50). (2017) Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines, [pdf] Tramel, E. W., Manoel, A., Caltagirone, F., Gabrié, M., & Krzakala, F. IEEE Information Theory Workshop (ITW), 265–269. (2016) Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy, [pdf] Gabrié, M., Tramel, E. W., & Krzakala, F. Advances in Neural Information Processing Systems 28, 640--648. (2015) |