2 citations · 4 across the 6 of their papers we have counts for
7 papers
Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning
Maximilian Negedly, Sebastian Falkner, Alessandro Coretti +1
Studying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are rare, observing them usually…
Generative Nested Sampling of Atomistic Thermodynamic Landscapes
Alessandro Coretti, Nico Unglert, Sebastian Falkner +2
Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-chain updates needed to decorrela…
Can DFT-trained neural network potentials reproduce structure, solvation, and water-exchange properties in aqueous magnesium solutions?
Sebastian Falkner, Pablo Montero de Hijes, Christoph Dellago +1
Magnesium ions play an essential role in many biological processes but remain challenging to model in biomolecular simulations. Despite considerable scientific effort, classical fo…
An Always-Accepting Algorithm for Transition Path Sampling
Magdalena Häupl, Sebastian Falkner, Peter G. Bolhuis +2
We present a one-way shooting algorithm for transition path sampling that accepts every proposed trajectory, yet samples the correct transition path ensemble for systems with overd…
Non-Markovian dynamics in ice nucleation
Pablo Montero de Hijes, Sebastian Falkner, Christoph Dellago
In simulation studies of crystallisation, the size of the largest crystalline nucleus is often used as a reaction coordinate to monitor the progress of the nucleation process. Here…
Revisiting Shooting Point Monte Carlo Methods for Transition Path Sampling
Sebastian Falkner, Alessandro Coretti, Baron Peters +2
Rare event sampling algorithms are essential for understanding processes that occur infrequently on the molecular scale, yet they are important for the long-time dynamics of comple…
Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems
Alessandro Coretti, Sebastian Falkner, Jan Weinreich +2
The paper by Noé et al. [F. Noé, S. Olsson, J. Köhler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can pr…