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Lattice Glass Models, and . Physical Review Letters, 88 (2): 025501+ (December 2001)Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias., , , and . NeurIPS, page 9330-9340. (2019)A jamming transition from under- to over-parametrization affects loss landscape and generalization., , , , , and . CoRR, (2018)On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3655-3663. PMLR, (2024)Phase transitions and complexity in computer science: an overview of the statistical physics approach to the random satisfiability problem, , and . Physica A: Statistical Mechanics and its Applications, (Apr 1, 2002)From Zero to Hero: How local curvature at artless initial conditions leads away from bad minima., , and . CoRR, (2024)Landscape Complexity for the Empirical Risk of Generalized Linear Models., , and . CoRR, (2019)Perspective: The glass transition, and . The Journal of Chemical Physics, 138 (12): 12A301+ (2013)Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models., , , , and . NeurIPS, page 8676-8686. (2019)Cooperative Behavior of Kinetically Constrained Lattice Gas Models of Glassy Dynamics, , and . Journal of Statistical Physics, 120 (1): 167--238 (Jul 28, 2005)