Cecilia Clementi | DeepAI

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Featured Co-authors

Klaus-Robert Müller
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∙ 02/14/2023

Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

Machine-learned coarse-grained (CG) models have the potential for simula...

0 Andreas Krämer, et al. ∙

∙ 02/01/2023

Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics

Coarse-grained (CG) molecular dynamics enables the study of biological p...

0 Marloes Arts, et al. ∙

∙ 12/14/2022

Machine Learning Coarse-Grained Potentials of Protein Thermodynamics

A generalized understanding of protein dynamics is an unsolved scientifi...

1 Maciej Majewski, et al. ∙

∙ 06/14/2021

Machine Learning Implicit Solvation for Molecular Dynamics

Accurate modeling of the solvent environment for biological molecules is...

0 Yaoyi Chen, et al. ∙

∙ 12/22/2020

TorchMD: A deep learning framework for molecular simulations

Molecular dynamics simulations provide a mechanistic description of mole...

0 Stefan Doerr, et al. ∙

∙ 07/22/2020

Coarse Graining Molecular Dynamics with Graph Neural Networks

Coarse graining enables the investigation of molecular dynamics for larg...

14 Brooke E. Husic, et al. ∙

∙ 05/04/2020

Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach

Gradient-domain machine learning (GDML) is an accurate and efficient app...

62 Jiang Wang, et al. ∙

∙ 11/22/2019

Machine learning for protein folding and dynamics

Many aspects of the study of protein folding and dynamics have been affe...

0 Frank Noé, et al. ∙

∙ 11/07/2019

Machine learning for molecular simulation

Machine learning (ML) is transforming all areas of science. The complex ...

0 Frank Noé, et al. ∙

∙ 09/23/2019

Data-driven approximation of the Koopman generator: Model reduction, system identification, and control

We derive a data-driven method for the approximation of the Koopman gene...

0 Stefan Klus, et al. ∙

∙ 08/12/2019

Tensor-based EDMD for the Koopman analysis of high-dimensional systems

Recent years have seen rapid advances in the data-driven analysis of dyn...

3 Feliks Nüske, et al. ∙

∙ 12/04/2018

Machine Learning of coarse-grained Molecular Dynamics Force Fields

Atomistic or ab-initio molecular dynamics simulations are widely used to...

0 Jiang Wang, et al. ∙

∙ 12/06/2017

Sparse learning of stochastic dynamic equations

With the rapid increase of available data for complex systems, there is ...

1 Lorenzo Boninsegna, et al. ∙

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