2 citations · 4 across the 11 of their papers we have counts for
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LiveCoMS Roundtable: Discussing Markov state models after two decades of development v1.0
Daniel M. Zuckerman, Gregory R. Bowman, Amedeo Caflisch +14
Markov state models (MSMs) play a central role in the analysis of molecular dynamics (MD) simulations for biomolecules, and MSM methodologies have been under continual development…
Machine learning kinetics from molecular dynamics data
Jonathan Weare, Aaron R. Dinner
Most molecular transitions occur on time scales far beyond direct molecular dynamics simulations. The committor, the probability that a configuration reaches a product state before…
Nuclear Quantum Effects as a Denoising Problem
Weizhou Wang, Jonathan Weare, Aaron R. Dinner
Nuclear quantum effects are rigorously captured by imaginary-time path integrals, which map the quantum Boltzmann distribution onto a ring polymer of classical replicas. Yet the nu…
Composing diffusion priors with explicit physical context via generative Gibbs sampling
Weizhou Wang, Jonathan Weare, Aaron R. Dinner
Pretrained diffusion models provide powerful learned priors, but in scientific sampling the target distribution often depends on physical context that is not fully represented by o…
Adaptive tensor train metadynamics for high-dimensional free energy exploration
Nils E. Strand, Siyao Yang, Yuehaw Khoo +1
A key challenge for molecular dynamics simulations is efficient exploration of free energy landscapes over relevant collective variables (CV). Common methods for enhancing sampling…
Quantum statistics from classical simulations via generative Gibbs sampling
Weizhou Wang, Xuanxi Zhang, Jonathan Weare +1
Accurate simulation of nuclear quantum effects is essential for molecular modeling but expensive using path integral molecular dynamics (PIMD). We present GG-PI, a ring-polymer-bas…