51 citations · 56 across the 12 of their papers we have counts for
4 papers · 1 filter
BU-MBAR: A hybrid solution strategy for the MBAR equations
Fabio Müller, Francesco Alesiani, Henrik Christiansen
The multi-state Bennett acceptance ratio (MBAR) equations combine the data collected under different thermodynamic conditions in a statistically optimal way. Due to their practical…
Hyperspatial Sampling: Circumventing Free-Energy Barriers via Replica Exchange with Extra Dimensions
Henrik Christiansen, Matheus Ferraz, Takashi Maruyama +1
Simulating systems with rugged free-energy landscapes remains a central challenge in computational physics and chemistry. We introduce hyperspatial replica exchange (HS-REX), an en…
Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations
Henrik Christiansen, Takashi Maruyama, Federico Errica +3
We present an end-to-end differentiable molecular simulation framework (DIMOS) for molecular dynamics and Monte Carlo simulations. DIMOS easily integrates machine-learning-based in…
Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials
Viktor Zaverkin, David Holzmüller, Henrik Christiansen +5
Efficiently creating a concise but comprehensive data set for training machine-learned interatomic potentials (MLIPs) is an under-explored problem. Active learning, which uses bias…