92 citations
- Centre National de la Recherche ScientifiqueFR7 papers
- Laboratoire de Chimie ThéoriqueFR7 papers
- Sorbonne UniversitéFR7 papers
- The University of Texas at AustinUS6 papers
- Institut Parisien de Chimie MoléculaireFR2 papers
- BNP Paribas (France)FR1 paper
- Carnegie Mellon UniversityUS1 paper
- Institut Universitaire de FranceFR1 paper
- Laboratoire de Biochimie ThéoriqueFR1 paper
- Laboratoire de Physique Théorique et Hautes EnergiesFR1 paper
- Laboratoire Jacques-Louis LionsFR1 paper
- Laboratoire Jean PerrinFR1 paper
7 papers
Lambda-ABF: Simplified, Portable, Accurate and Cost-effective Alchemical Free Energy Computations
Louis Lagardère, Lise Maurin, Olivier Adjoua +4
We introduce an efficient and robust method to compute alchemical free energy differences, resulting from the application of multiple walker Adaptive Biasing Force (ABF) in conjunc…
Smooth Particle Mesh Ewald-integrated stochastic Lanczos Many-body Dispersion algorithm
Pier P. Poier, Louis Lagardère, Jean-Philip Piquemal
We derive and implement an alternative formulation of the Stochastic Lanczos algorithm to be employed in connection with the Many-Body Dispersion model (MBD). Indeed, this formulat…
Generalized Many-Body Dispersion Correction through Random-phase Approximation for Chemically Accurate Density Functional Theory
Pier Paolo Poier, Louis Lagardère, Jean-Philip Piquemal
We extend our recently proposed Deep Learning-aided many-body dispersion (DNN-MBD) model to quadrupole polarizability (Q) terms using a generalized Random Phase Approximation (RPA)…
Scalable Hybrid Deep Neural Networks/Polarizable Potentials Biomolecular Simulations including long-range effects
Théo Jaffrelot Inizan, Thomas Plé, Olivier Adjoua +5
Deep-HP is a scalable extension of the \TinkerHP\ multi-GPUs molecular dynamics (MD) package enabling the use of Pytorch/TensorFlow Deep Neural Networks (DNNs) models. Deep-HP incr…
Accurate Deep Learning-aided Density-free Strategy for Many-Body Dispersion-corrected Density Functional Theory
Pier Paolo Poier, Théo Jaffrelot Inizan, Olivier Adjoua +2
Using a Deep Neuronal Network model (DNN) trained on the large ANI-1 data set of small organic molecules, we propose a transferable density-free many-body dispersion model (DNN-MBD…
Development of the Quantum Inspired SIBFA Many-Body Polarizable Force Field: Enabling Condensed Phase Molecular Dynamics Simulations
Sehr Naseem-Khan, Louis Lagardère, Christophe Narth +4
We present the extension of the SIBFA (Sum of Interactions Between Fragments Ab initio Computed many-body polarizable force field to condensed phase Molecular Dynamics (MD) simulat…