Magnus Petersen
@omorfiamorphism.bsky.social
DL × Computational Physics: Diffusion/Flow Matching for molecular dynamics, statistical physics for DL and vice versa! Cellular automata hobbyist 👾 Covino Lab
People I know who don't work in tech have not even heard of Anthropic. That might be the issue, also for non-technical tasks, it's very hard to discern which model is really "better"
August 5, 2025 at 1:45 PM
People I know who don't work in tech have not even heard of Anthropic. That might be the issue, also for non-technical tasks, it's very hard to discern which model is really "better"
Thanks! Actually had a chat with Sanjeev at his poster yesterday, great stuff! I think the amortization of these kinds of methods with pre-trained generative models is actually very promising! Will update the arxiv with this work soon
April 28, 2025 at 9:46 AM
Thanks! Actually had a chat with Sanjeev at his poster yesterday, great stuff! I think the amortization of these kinds of methods with pre-trained generative models is actually very promising! Will update the arxiv with this work soon
Link: arxiv.org/abs/2504.16381
Very cool related work: Doob's Lagrangian (Du et al., 2024): arxiv.org/abs/2410.07974 Implicit Neural Representations for Chemical Reaction Paths (Ramakrishnan et al., 2025): arxiv.org/abs/2502.15843
Very cool related work: Doob's Lagrangian (Du et al., 2024): arxiv.org/abs/2410.07974 Implicit Neural Representations for Chemical Reaction Paths (Ramakrishnan et al., 2025): arxiv.org/abs/2502.15843
PINN-MEP: Continuous Neural Representations for Minimum-Energy Path Discovery in Molecular Systems
Characterizing conformational transitions in physical systems remains a fundamental challenge in the computational sciences. Traditional sampling methods like molecular dynamics (MD) or MCMC often str...
arxiv.org
April 27, 2025 at 4:26 PM
Link: arxiv.org/abs/2504.16381
Very cool related work: Doob's Lagrangian (Du et al., 2024): arxiv.org/abs/2410.07974 Implicit Neural Representations for Chemical Reaction Paths (Ramakrishnan et al., 2025): arxiv.org/abs/2502.15843
Very cool related work: Doob's Lagrangian (Du et al., 2024): arxiv.org/abs/2410.07974 Implicit Neural Representations for Chemical Reaction Paths (Ramakrishnan et al., 2025): arxiv.org/abs/2502.15843
We represent a transition path as a continuous neural mapping and minimize an Onsager-Machlup-action-derived, simple, and scalable loss - literally just the sum of energies along the sampled neural path!
April 27, 2025 at 4:26 PM
We represent a transition path as a continuous neural mapping and minimize an Onsager-Machlup-action-derived, simple, and scalable loss - literally just the sum of energies along the sampled neural path!