9 citations · 14 across the 3 of their papers we have counts for
4 papers
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials
Cas van der Oord, Matthias Sachs, Dávid Péter Kovács +2
Data-driven interatomic potentials have emerged as a powerful class of surrogate models for {\it ab initio} potential energy surfaces that are able to reliably predict macroscopic…
Efficient Numerical Algorithms for the Generalized Langevin Equation
Benedict Leimkuhler, Matthias Sachs
We study the design and implementation of numerical methods to solve the generalized Langevin equation (GLE) focusing on canonical sampling properties of numerical integrators. For…
Non-reversible Markov chain Monte Carlo for sampling of districting maps
Gregory Herschlag, Jonathan C. Mattingly, Matthias Sachs +1
Evaluating the degree of partisan districting (Gerrymandering) in a statistical framework typically requires an ensemble of districting plans which are drawn from a prescribed prob…
Ergodic properties of quasi-Markovian generalized Langevin equations with configuration dependent noise and non-conservative force
Benedict Leimkuhler, Matthias Sachs
We discuss the ergodic properties of quasi-Markovian stochastic differential equations, providing general conditions that ensure existence and uniqueness of a smooth invariant dist…