Many questions of fundamental interest in today's science can be formulated as inference
problems: some partial, or noisy, observations are performed over a set of variables and the …

Mode-coupling theory is an approach to the study of complex behavior in the supercooled
liquids which developed from the idea of a nonlinear feedback mechanism. From the …

We study the scaling limits of stochastic gradient descent (SGD) with constant step-size in
the high-dimensional regime. We prove limit theorems for the trajectories of summary …

Ecological communities in heterogeneous environments assemble through the combined
effect of species interaction and migration. Understanding the effect of these processes on …

Recent years witnessed the development of powerful generative models based on flows,
diffusion, or autoregressive neural networks, achieving remarkable success in generating …

Motivated by advances in the field of active matter where nonequilibrium forcing has been
shown to activate new assembly pathways, here we study how nonequilibrium driving in …

This review reports on the research done during past years on violations of the fluctuation–
dissipation theorem (FDT) in glassy systems. It is focused on the existence of a quasi …

We consider the problem of estimating a large rank‐one tensor u⊗ k∈(ℝn)⊗ k, k≥ 3, in
Gaussian noise. Earlier work characterized a critical signal‐to‐noise ratio λ Bayes= O (1) …

We study a class of deterministic flows in ${\mathbb R}^{d\times k} $, parametrized by a
random matrix ${\boldsymbol X}\in {\mathbb R}^{n\times d} $ with iid centered subgaussian …

We consider the problem of finding nearly optimal solutions of optimization problems with
random objective functions. Such problems arise widely in the theory of random graphs …