Cover Image

Transferable Generative Models Bridge Femtosecond to Nanosecond Time-Step Molecular Dynamics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Diez, Juan Viguera, Schreiner, Mathias, Olsson, Simon
Format:	Preprint
Published:	2025
Subjects:	Chemical Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Boltzmann priors for Implicit Transfer Operators
by: Diez, Juan Viguera, et al.
Published: (2024)

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces
by: Gouraud, Nicolaï, et al.
Published: (2026)

Generative flow-based warm start of the variational quantum eigensolver
by: Zou, Hang, et al.
Published: (2025)

Thermodynamic Interpolation: A generative approach to molecular thermodynamics and kinetics
by: Moqvist, Selma, et al.
Published: (2024)

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning
by: Ren, Yuxuan, et al.
Published: (2024)

Transfer Learning for Molecular Property Predictions from Small Data Sets
by: Kirschbaum, Thorren, et al.
Published: (2024)

Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery
by: Xu, Guikun, et al.
Published: (2025)

Molecular Learning Dynamics
by: Gusev, Yaroslav, et al.
Published: (2025)

Force-Guided Bridge Matching for Full-Atom Time-Coarsened Dynamics of Peptides
by: Yu, Ziyang, et al.
Published: (2024)

Femtosecond Core-Level Charge Transfer
by: Neville, Simon P., et al.
Published: (2024)

Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
by: Kim, Dongki, et al.
Published: (2025)

Transferable Boltzmann Generators
by: Klein, Leon, et al.
Published: (2024)

Generative Pseudo-Force Fields for Molecular Generation
by: Hessmann, Stefaan Simon Pierre, et al.
Published: (2026)

GP-MoLFormer: A Foundation Model For Molecular Generation
by: Ross, Jerret, et al.
Published: (2024)

Training-Free Guidance for Discrete Diffusion Models for Molecular Generation
by: Kerby, Thomas J., et al.
Published: (2024)

Zero Shot Molecular Generation via Similarity Kernels
by: Elijošius, Rokas, et al.
Published: (2024)

Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators
by: Shteingolts, S. A., et al.
Published: (2026)

Operator Forces For Coarse-Grained Molecular Dynamics
by: Klein, Leon, et al.
Published: (2025)

MUBen: Benchmarking the Uncertainty of Molecular Representation Models
by: Li, Yinghao, et al.
Published: (2023)

Efficient Parallelization of Message Passing Neural Network Potentials for Large-scale Molecular Dynamics
by: Xia, Junfan, et al.
Published: (2025)

Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion Model
by: Xiang, Yuran, et al.
Published: (2024)

Meta-Learning Linear Models for Molecular Property Prediction
by: Pimonova, Yulia, et al.
Published: (2025)

A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
by: Ji, Shengjiao, et al.
Published: (2025)

NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra
by: Ottomano, Federico, et al.
Published: (2025)

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
by: Cao, Zhonglin, et al.
Published: (2025)

Chemistry-Enhanced Diffusion-Based Framework for Small-to-Large Molecular Conformation Generation
by: Zhu, Yifei, et al.
Published: (2025)

Knowledge-Reuse Transfer Learning Methods in Molecular and Material Science
by: Chen, An, et al.
Published: (2024)

Deep Learning Foundation Models from Classical Molecular Descriptors
by: Burns, Jackson W., et al.
Published: (2025)

Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracy
by: Woo, Jeheon, et al.
Published: (2024)

Lightweight Geometric Deep Learning for Molecular Modelling in Catalyst Discovery
by: Geitner, Patrick
Published: (2024)

Active Learning Enables Extrapolation in Molecular Generative Models
by: Antoniuk, Evan R., et al.
Published: (2025)

Spectral Analysis of Molecular Kernels: When Richer Features Do Not Guarantee Better Generalization
by: Jamali, Asma, et al.
Published: (2025)

Uni-Mol3: A Multi-Molecular Foundation Model for Advancing Organic Reaction Modeling
by: Wu, Lirong, et al.
Published: (2025)

Automated Molecular Concept Generation and Labeling with Large Language Models
by: Zhang, Zimin, et al.
Published: (2024)

FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms
by: Gharakhanyan, Vahe, et al.
Published: (2025)

MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry
by: Batatia, Ilyes, et al.
Published: (2026)

Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
by: Boiko, Daniil A., et al.
Published: (2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets
by: Koziarski, Michał, et al.
Published: (2024)

From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
by: Devergne, Timothée, et al.
Published: (2024)

RoFt-Mol: Benchmarking Robust Fine-Tuning with Molecular Graph Foundation Models
by: Liu, Shikun, et al.
Published: (2025)