Starting at the mesoscopic level with a general formulation of stochastic thermodynamics in
terms of Markov jump processes, the scaling conditions that ensure the emergence of a …

We review the concept of dynamical ensembles in nonequilibrium statistical mechanics as
specified from an action functional or Lagrangian on spacetime. There, under local detailed …

Solving inverse problems without the use of derivatives or adjoints of the forward model is
highly desirable in many applications arising in science and engineering. In this paper we …

One common feature of new emerging technologies is the fusion of the very small (nano)
scale and the large scale engineering. The classical environment provided by single scale …

Bayesian inference problems require sampling or approximating high-dimensional
probability distributions. The focus of this paper is on the recently introduced Stein …

We propose a thermodynamics-based learning strategy for non-equilibrium evolution
equations based on Onsager's variational principle, which allows us to write such PDEs in …

We propose a computational method (with acronym ALDI) for sampling from a given target
distribution based on first-order (overdamped) Langevin dynamics which satisfies the …

We have created a functional framework for a class of non-metric gradient systems. The
state space is a space of nonnegative measures, and the class of systems includes the …

Chemical reaction networks offer a natural nonlinear generalization of linear Markov jump
processes on a finite state-space. In this paper, we analyze the dynamical large deviations …

We give a systematic derivation of positive lower bounds for the expected entropy
production (EP) rate in classical statistical mechanical systems obeying a dynamical large …