Author

Christoph Dellago

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Preprint Aug 2026

Nonadiabatic Forward-Flux Sampling of Rare Molecular Gas-Phase Ammonia Photodissociation

Simulating rare events in photochemistry by brute-force surface hopping is computationally prohibitive: most propagated trajectories either remain nonreactive or follow dominant relaxation channels, while the reaction of interest may occur with very low probability. Path sampling methods have long addressed this proble...

Madlen Maria Reiner, Johannes C. B. Dietschreit, L. González et al. · 0 citations

#machine learning Preprint Sep 2026

Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning

GenAIMMD is introduced, an iterative algorithm that actively and self-consistently learns the ideal reaction coordinate (the committor) and trains a conditioned Boltzmann Generator to sample from arbitrary bias windows along it, providing a correlation-free and fully parallelizable path sampling scheme that does not re...

Maximilian Negedly, Sebastian Falkner, A. Coretti et al. · 0 citations

#machine learning Preprint Sep 2026

Generative Nested Sampling of Atomistic Thermodynamic Landscapes

This work introduces NS-Flows: a single conditional normalizing flow, conditioned on the NS energy bound and trained on a sliding window of recent live sets, that replaces MCMC by direct parallel draws corrected by importance-weighted rejection resampling, allowing flow training without structured priors or a pre-exist...

A. Coretti, N. Unglert, Sebastian Falkner et al. · 0 citations