Statistically Optimal Force Aggregation for Coarse-Graining Molecular
Dynamics

Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

14 February 2023

Andreas Krämer

Aleksander E. P. Durumeric

Frank Noé

Papers citing "Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics"

8 / 8 papers shown

Title
Universally applicable and tunable graph-based coarse-graining for Machine learning force fields Christoph Brunken Sebastien Boyer Mustafa Omar Martin Maarand Olivier Peltre Solal Attias Bakary Diallo Anastasia Markina Olaf Othersen Oliver E. Bent OOD AI4CE 49 0 0 24 Mar 2025
AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics Antonio Mirarchi Raúl P. Peláez Guillem Simeon Gianni De Fabritiis 23 3 0 26 Sep 2024
Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks Emily Shinkle Aleksandra Pachalieva Riti Bahl Sakib Matin Brendan Gifford G. Craven Nicholas Lubbers 29 2 0 17 Jun 2024
Navigating protein landscapes with a machine-learned transferable coarse-grained model N. Charron Felix Musil Andrea Guljas Yaoyi Chen Klara Bonneau ... B. Husic Ankit Patel Gianni De Fabritiis Frank Noé C. Clementi AI4CE 16 13 0 27 Oct 2023
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces Michael S. Jones Kirill Shmilovich Andrew L. Ferguson DiffM 36 12 0 23 Jul 2023
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics M. Schreiner Ole Winther Simon Olsson OOD AI4CE 41 13 0 29 May 2023
Contrastive Learning of Coarse-Grained Force Fields Xinqiang Ding Bin W. Zhang 35 21 0 22 May 2022
Coarse Graining Molecular Dynamics with Graph Neural Networks B. Husic N. Charron Dominik Lemm Jiang Wang Adria Pérez ... Yaoyi Chen Simon Olsson Gianni De Fabritiis Frank Noé C. Clementi AI4CE 40 158 0 22 Jul 2020