ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.12946
  4. Cited By
Investigation of Machine Learning-based Coarse-Grained Mapping Schemes
  for Organic Molecules

Investigation of Machine Learning-based Coarse-Grained Mapping Schemes for Organic Molecules

26 September 2022
Dimitris Nasikas
E. Ricci
George Giannakopoulos
V. Karkaletsis
D. Theodorou
Niki Vergadou
ArXivPDFHTML

Papers citing "Investigation of Machine Learning-based Coarse-Grained Mapping Schemes for Organic Molecules"

3 / 3 papers shown
Title
Universally applicable and tunable graph-based coarse-graining for Machine learning force fields
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
Developing Machine-Learned Potentials for Coarse-Grained Molecular
  Simulations: Challenges and Pitfalls
Developing Machine-Learned Potentials for Coarse-Grained Molecular Simulations: Challenges and Pitfalls
E. Ricci
George Giannakopoulos
V. Karkaletsis
D. Theodorou
Niki Vergadou
AI4CE
30
9
0
26 Sep 2022
Coarse Graining Molecular Dynamics with Graph Neural Networks
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
1