47 citations · 47 across the 6 of their papers we have counts for
4 papers · 1 filter
Navigating committor landscape of biomolecules with a general pairwise interaction model
Jintu Zhang, Zichang Jin, Huifeng Zhao +5
Sampling rare conformation transitions between metastable states is a central challenge in atomistic simulations. While the committor function serve as an ideal reaction coordinate…
SelfTICA: contrastive learning of dynamical representations for rare-event sampling and characterization
Kai Zhu, Jintu Zhang, Pietro Novelli +2
Rare events govern many important molecular processes but remain difficult to characterize within accessible simulation timescales. This challenge has motivated machine-learning me…
Committors without Descriptors
Peilin Kang, Jintu Zhang, Enrico Trizio +2
The study of rare events is one of the major challenges in atomistic simulations, and several enhanced sampling methods towards its solution have been proposed. Recently, it has be…
Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
Kai Zhu, Enrico Trizio, Jintu Zhang +4
Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constraine…