2 citations · 4 across the 11 of their papers we have counts for
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Hierarchical geometric deep learning enables scalable analysis of molecular dynamics
Zihan Pengmei, Spencer C. Guo, Chatipat Lorpaiboon +1
Molecular dynamics simulations can generate atomically detailed trajectories of complex systems, but analyzing these dynamics can be challenging when systems lack well-established…
An exact multiple-time-step variational formulation for the committor and the transition rate
Chatipat Lorpaiboon, Jonathan Weare, Aaron R. Dinner
For a transition between two stable states, the committor is the probability that the dynamics leads to one stable state before the other. It can be estimated from trajectory data…
Mitigating mode collapse in normalizing flows by annealing with an adaptive schedule: Application to parameter estimation
Yihang Wang, Chris Chi, Aaron R. Dinner
Normalizing flows (NFs) provide uncorrelated samples from complex distributions, making them an appealing tool for parameter estimation. However, the practical utility of NFs remai…
Characterizing nonlinear dynamics by contrastive cartography
Nicolas Romeo, Chris Chi, Aaron R. Dinner +1
The qualitative study of dynamical systems using bifurcation theory is key to understanding systems from biological clocks and neurons to physical phase transitions. Data generated…