REVIEW 1 cited by
Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
The paper by No\'e et al. [F. No\'e, S. Olsson, J. K\"ohler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can produce unbiased independent samples of many-body systems. They can generate equilibrium configurations from different metastable states, compute relative stabilities between different structures of proteins or other organic molecules, and discover new states. In this commentary, we motivate the necessity for a new generation of sampling methods beyond molecular dynamics, explain the methodology, and give our perspective on the future role of BGs.
Forward citations
Cited by 1 Pith paper
-
BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps
BoostMD accelerates MLFF molecular dynamics by predicting energy changes from previous-step node features and positional displacements, reporting 8x speedup and matching the reference model's sampled free energy surfa...
Discussion (0). Continue with ORCID to comment.