15 citations · 24 across the 4 of their papers we have counts for
4 papers
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…
Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics
Zihan Pengmei, Chatipat Lorpaiboon, Spencer C. Guo +2
Identifying informative low-dimensional features that characterize dynamics in molecular simulations remains a challenge, often requiring extensive manual tuning and system-specifi…
Accurate estimates of dynamical statistics using memory
Chatipat Lorpaiboon, Spencer C. Guo, John Strahan +2
Many chemical reactions and molecular processes occur on timescales that are significantly longer than those accessible by direct simulation. One successful approach to estimating…
Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction
John Strahan, Spencer C. Guo, Chatipat Lorpaiboon +2
Understanding dynamics in complex systems is challenging because there are many degrees of freedom, and those that are most important for describing events of interest are often no…