Zobrazeno 1 - 10
of 198
pro vyhledávání: '"ARISTOFF, P. A."'
In the study of stochastic systems, the committor function describes the probability that a system starting from an initial configuration $x$ will reach a set $B$ before a set $A$. This paper introduces an efficient and interpretable algorithm for ap
Externí odkaz:
http://arxiv.org/abs/2405.10410
Autor:
Seelinger, Linus, Reinarz, Anne, Lykkegaard, Mikkel B., Akers, Robert, Alghamdi, Amal M. A., Aristoff, David, Bangerth, Wolfgang, Bénézech, Jean, Diez, Matteo, Frey, Kurt, Jakeman, John D., Jørgensen, Jakob S., Kim, Ki-Tae, Kent, Benjamin M., Martinelli, Massimiliano, Parno, Matthew, Pellegrini, Riccardo, Petra, Noemi, Riis, Nicolai A. B., Rosenfeld, Katherine, Serani, Andrea, Tamellini, Lorenzo, Villa, Umberto, Dodwell, Tim J., Scheichl, Robert
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 this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-l
Externí odkaz:
http://arxiv.org/abs/2402.13768
Molecular dynamics (MD) and enhanced sampling simulations have become fundamental tools for studying biomolecular events. A significant challenge in these simulations is ensuring that sampled configurations and transitions converge to the stationary
Externí odkaz:
http://arxiv.org/abs/2401.05597
This article introduces an advanced Koopman mode decomposition (KMD) technique -- coined Featurized Koopman Mode Decomposition (FKMD) -- that uses delay embedding and a learned Mahalanobis distance to enhance analysis and prediction of high dimension
Externí odkaz:
http://arxiv.org/abs/2312.09146
Stochastic dynamics, such as molecular dynamics, are important in many scientific applications. However, summarizing and analyzing the results of such simulations is often challenging, due to the high dimension in which simulations are carried out, a
Externí odkaz:
http://arxiv.org/abs/2305.20083
Publikováno v:
J.Chem.Phys. 158 (2023) 014108
The weighted ensemble (WE) method, an enhanced sampling approach based on periodically replicating and pruning trajectories in a set of parallel simulations, has grown increasingly popular for computational biochemistry problems, due in part to impro
Externí odkaz:
http://arxiv.org/abs/2206.14943
Markov state models (MSMs) have been broadly adopted for analyzing molecular dynamics trajectories, but the approximate nature of the models that results from coarse-graining into discrete states is a long-known limitation. We show theoretically that
Externí odkaz:
http://arxiv.org/abs/2105.13402
Autor:
Aristoff, David, Bangerth, Wolfgang
Bayesian methods have been widely used in the last two decades to infer statistical properties of spatially variable coefficients in partial differential equations from measurements of the solutions of these equations. Yet, in many cases the number o
Externí odkaz:
http://arxiv.org/abs/2102.07263
We explore whether splitting and killing methods can improve the accuracy of Markov chain Monte Carlo (MCMC) estimates of rare event probabilities, and we make three contributions. First, we prove that "weighted ensemble" is the only splitting and ki
Externí odkaz:
http://arxiv.org/abs/2011.13899
Autor:
Aristoff, David
Publikováno v:
J. Appl. Probab. 59, 152-166 (2022)
We study weighted ensemble, an interacting particle method for sampling distributions of Markov chains that has been used in computational chemistry since the 1990s. Many important applications of weighted ensemble require the computation of long tim
Externí odkaz:
http://arxiv.org/abs/1906.00856