Fetching the paper…
Reading the bibliography…
We consider the problem of sampling transition paths between two given metastable states of a molecular system, e.g.
Über die umkehrung der naturgesetze
Erwin Schrödinger · 1931
Earlier work this paper cites.
Sur la théorie relativiste de l’électron et l’interprétation de la mécanique quantique
Erwin Schrödinger · 1932
Earlier work this paper cites.
Transformations of weiner integrals under translations
Robert H Cameron and William T Martin · 1944
Earlier work this paper cites.
Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling
Glenn M Torrie and John P Valleau · 1977
Earlier work this paper cites.
Constrained reaction coordinate dynamics for the simulation of rare events
E.A. Carter, Giovanni Ciccotti, James T. Hynes, and Raymond Kapral · 1989
Earlier work this paper cites.
Local elevation: A method for improving the searching properties of molecular dynamics simulation
Thomas Huber, Andrew E. Torda, and Wilfred F. Van Gunsteren · 1994
Earlier work this paper cites.
Predicting slow structural transitions in macromolecular systems: Conformational flooding
Helmut Grubmüller · 1995
Earlier work this paper cites.
A smooth particle mesh Ewald method
Ulrich Essmann, Lalith Perera, Max L Berkowitz, Tom Darden, Hsing Lee, and Lee G Pedersen · 1995
Earlier work this paper cites.
A method for accelerating the molecular dynamics simulation of infrequent events
Arthur F. Voter · 1997
Earlier work this paper cites.
Transition path sampling and the calculation of rate constants
Christoph Dellago, Peter G. Bolhuis, Félix S. Csajka, and David Chandler · 1998
Earlier work this paper cites.
Free energy from constrained molecular dynamics
Michiel Sprik and Giovanni Ciccotti · 1998
Earlier work this paper cites.
Reaction coordinates of biomolecular isomerization
Peter G. Bolhuis, Christoph Dellago, and David Chandler · 2000
Earlier work this paper cites.
A climbing image nudged elastic band method for finding saddle points and minimum energy paths
Graeme Henkelman, Blas P. Uberuaga, and Hannes Jónsson · 2000
Earlier work this paper cites.
Understanding molecular simulation: from algorithms to applications , volume 1
Daan Frenkel and Berend Smit · 2001
Earlier work this paper cites.
Calculating free energies using average force
Eric Darve and Andrew Pohorille · 2001
Earlier work this paper cites.
Efficient, Multiple-Range Random Walk Algorithm to Calculate the Density of States
Fugao Wang and D. P. Landau · 2001
Earlier work this paper cites.
Transition path sampling: Throwing ropes over rough mountain passes, in the dark
Peter G Bolhuis, David Chandler, Christoph Dellago, and Phillip L Geissler · 2002
Earlier work this paper cites.
Escaping free-energy minima
Alessandro Laio and Michele Parrinello · 2002
Cited alongside, same era.
10 residue folded peptide designed by segment statistics
Shinya Honda, Kazuhiko Yamasaki, Yoshito Sawada, and Hisayuki Morii · 2004
Cited alongside, same era.
Path integrals and symmetry breaking for optimal control theory
Hilbert J Kappen · 2005
Cited alongside, same era.
Reproducible polypeptide folding and structure prediction using molecular dynamics simulations
M Marvin Seibert, Alexandra Patriksson, Berk Hess, and David Van Der Spoel · 2005
Cited alongside, same era.
Folding free-energy landscape of a 10-residue mini-protein, chignolin
Daisuke Satoh, Kentaro Shimizu, Shugo Nakamura, and Tohru Terada · 2006
Cited alongside, same era.
Accurate sampling using Langevin dynamics
Giovanni Bussi and Michele Parrinello · 2007
Cited alongside, same era.
Adaptive importance sampling for control and inference
Hilbert Johan Kappen and Hans Christian Ruiz · 2016
Later among the works it cites.
On the relation between optimal transport and Schrödinger bridges: A stochastic control viewpoint
Yongxin Chen, Tryphon T Georgiou, and Michele Pavon · 2016
Later among the works it cites.
Group equivariant convolutional networks
Taco Cohen and Max Welling · 2016
Later among the works it cites.
Stochastic Neural Network Approach for Learning High-Dimensional Free Energy Surfaces
Elia Schneider, Luke Dai, Robert Q. Topper, Christof Drechsel-Grau, and Mark E. Tuckerman · 2017
Later among the works it cites.
OpenMM 7: Rapid development of high performance algorithms for molecular dynamics
Peter Eastman, Jason Swails, John D Chodera, Robert T McGibbon, Yutong Zhao, Kyle A Beauchamp, Lee-Ping Wang, Andrew C Simmonett, Matthew P Harrigan, Chaya D Stern, et al · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
An introduction to stochastic control theory, path integrals and reinforcement learning
Hilbert J Kappen · 2007
Cited alongside, same era.
Folding dynamics of 10-residue β \beta -hairpin peptide chignolin
Atsushi Suenaga, Tetsu Narumi, Noriyuki Futatsugi, Ryoko Yanai, Yousuke Ohno, Noriaki Okimoto, and Makoto Taiji · 2007
Cited alongside, same era.
Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method
Alessandro Barducci, Giovanni Bussi, and Michele Parrinello · 2008
Cited alongside, same era.
Improved side-chain torsion potentials for the Amber ff99SB protein force field
Kresten Lindorff-Larsen, Stefano Piana, Kim Palmo, Paul Maragakis, John L Klepeis, Ron O Dror, and David E Shaw · 2010
Cited alongside, same era.
Exploring the folding free energy landscape of a β \beta -hairpin miniprotein, chignolin, using multiscale free energy landscape calculation method
Ryuhei Harada and Akio Kitao · 2011
Cited alongside, same era.
How fast-folding proteins fold
Kresten Lindorff-Larsen, Stefano Piana, Ron O Dror, and David E Shaw · 2011
Cited alongside, same era.
Scott A. Hollingsworth and Ron O. Dror · 2018
Later among the works it cites.
Transferable Neural Networks for Enhanced Sampling of Protein Dynamics
Mohammad M. Sultan, Hannah K. Wayment-Steele, and Vijay S. Pande · 2018
Later among the works it cites.
Machine Learning Force Fields
Oliver T. Unke, Stefan Chmiela, Huziel E. Sauceda, Michael Gastegger, Igor Poltavsky, Kristof T. Schütt, Alexandre Tkatchenko, and Klaus-Robert Müller · 2021
Later among the works it cites.
Discovering collective variables of molecular transitions via genetic algorithms and neural networks
Ferry Hooft, Alberto Pérez de Alba Ortíz, and Bernd Ensing · 2021
Later among the works it cites.
Reinforcement learning of rare diffusive dynamics
Avishek Das, Dominic C Rose, Juan P Garrahan, and David T Limmer · 2021
Later among the works it cites.
Solving schrödinger bridges via maximum likelihood
Francisco Vargas, Pierre Thodoroff, Austen Lamacraft, and Neil Lawrence · 2021
Later among the works it cites.
Diffusion Schrödinger bridge with applications to score-based generative modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, and Arnaud Doucet · 2021
Later among the works it cites.
Learning gradient fields for molecular conformation generation
Chence Shi, Shitong Luo, Minkai Xu, and Jian Tang · 2021
Later among the works it cites.
E(n) equivariant graph neural networks
Victor Garcia Satorras, Emiel Hoogeboom, and Max Welling · 2021
Later among the works it cites.
How to determine accurate conformational ensembles by metadynamics metainference: a chignolin study case
Cristina Paissoni and Carlo Camilloni · 2021
Later among the works it cites.
Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gomez-Bombarelli, and Tommi Jaakkola · 2022
Closest in time.