arXiv AI July 1, 2026 By Wenjie Xi

Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout

arXiv:2606. 30687v1 Announce Type: cross Abstract: Diffusion models are increasingly utilized for modeling molecular structures and conformational ensembles, yet the thermodynamic meaning of their learned representations and scores remains elusive.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

diffusion

arXiv Machine Learning

Jul 7

AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

arXiv:2607. 03513v1 Announce Type: cross Abstract: We present AquaGen, the first all-atom, explicit solvent, periodic-boundary-condition-aware generative model that produces molecular configurations from the Boltzmann distribution at a fraction of the cost of molecular dynamics (MD).

By Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang, Kerstin Klaeser, Cristian Gabellini, Nikhil Shenoy, Francesco Di Giovanni, Prudencio Tossou

safety

arXiv AI

Jun 15

A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction

arXiv:2606. 14498v1 Announce Type: cross Abstract: Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels, and electronic-structure observables that energy-only surrogates cannot resolve.

By Yunhong Lou, Xihang Yue, Xinran Wei, Tianqi Deng, Linchao Zhu

fine-tuning benchmarks

arXiv AI

Jun 30

Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models

arXiv:2602. 16634v2 Announce Type: replace-cross Abstract: The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation.

By Yu Xie, Ludwig Winkler, Lixin Sun, Sarah Lewis, Adam E. Foster, Jos\'e Jim\'enez Luna, Tim Hempel, Michael Gastegger, Yaoyi Chen, Iryna Zaporozhets, Cecilia Clementi, Christopher M. Bishop, Frank No\'e

diffusion

arXiv AI

Jun 11

FreeBridge: Variational Schr\"odinger Bridges for Cellular Transition Dynamics

arXiv:2606. 11286v1 Announce Type: cross Abstract: High-content imaging assays quantify cellular responses to chemical and genetic perturbations, yet continuous trajectories of individual cells are unobservable because cells are chemically fixed at acquisition.

By Xurui Wang, Qin Ren, Jun Ma, Haibin Ling, Chenyu You

safety

arXiv Machine Learning

Jun 4

Gradient estimators for parameter inference in discrete stochastic kinetic models

arXiv:2604. 02121v2 Announce Type: replace-cross Abstract: Stochastic kinetic models are ubiquitous in physics, yet inferring their parameters from experimental data remains challenging.

By Ludwig Burger, Annalena Kofler, Lukas Heinrich, Ulrich Gerland

arXiv Machine Learning

Jul 20

DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales

arXiv:2607. 15309v1 Announce Type: cross Abstract: Proteins function through coordinated motion across multiple spatial and temporal scales, underpinning processes such as ligand binding, allostery, and catalysis.

By Kaihui Cheng, Zhiqiang Cai, Peng Tu, Yisong Yao, Limei Han, Libo Wu, Siyu Zhu, Tzuhsiung Yang, Yuan Qi

benchmarks

Related stories

AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction

Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models

FreeBridge: Variational Schr\"odinger Bridges for Cellular Transition Dynamics

Gradient estimators for parameter inference in discrete stochastic kinetic models

DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales