29 citations · 246 across the 34 of their papers we have counts for
35 papers
Markov state models revisited: Principles and algorithms for unbiased observables
David Aristoff, Robert J. Webber, Daniel M. Zuckerman
Markov state models (MSMs) have become ubiquitous tools for analyzing molecular dynamics (MD) simulations because of their simple, powerful premise: although complete MD sampling m…
Reducing Weighted Ensemble Variance With Optimal Trajectory Management
Won Hee Ryu, John D. Russo, Mats S. Johnson +7
Weighted ensemble (WE) is an enhanced path-sampling method that is conceptually simple, widely applicable, and statistically exact. In a WE simulation, an ensemble of trajectories…
The fast committor machine: Interpretable prediction with kernels
D. Aristoff, M. Johnson, G. Simpson +1
In the study of stochastic systems, the committor function describes the probability that a system starting from an initial configuration will reach a set before a set .…
Democratizing Uncertainty Quantification
Linus Seelinger, Anne Reinarz, Mikkel B. Lykkegaard +22
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In thi…
RiteWeight: Randomized Iterative Trajectory Reweighting for Steady-State Distributions Without Discretization Error
Sagar Kania, Robert J. Webber, Gideon Simpson +2
A significant challenge in molecular dynamics (MD) simulations is ensuring that sampled configurations converge to the equilibrium or nonequilibrium stationary distribution of inte…
Featurizing Koopman Mode Decomposition For Robust Forecasting
David Aristoff, Jeremy Copperman, Nathan Mankovich +1
This article introduces an advanced Koopman mode decomposition (KMD) technique -- coined Featurized Koopman Mode Decomposition (FKMD) -- that uses delay embedding and a learned Mah…