Raimondas Galvelis

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Machine Learning

Single Molecule

Molecular Dynamics

Top Venues

Journal of chemical information and modeling

The journal of physical chemistry. B

Scientific data

Journal of chemical theory and computation

This page only lists publications with an associated author ORCID identifier.

Publications

Raul P Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E Markland, Gianni De Fabritiis
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. Journal of chemical theory and computation 20 (10) (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling 64 (5) (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling 64 (5) (2024)
Raul P Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E Markland, Gianni De Fabritiis
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. Journal of chemical theory and computation (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling 64 (5) (2024)
Raul P Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E Markland, Gianni De Fabritiis
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. Journal of chemical theory and computation 20 (10) (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling 64 (5) (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling (2024)
Raul P Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E Markland, Gianni De Fabritiis
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. Journal of chemical theory and computation (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling (2024)
Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D Chodera, Thomas E Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. Journal of chemical information and modeling 64 (5) (2024)
Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter Eastman, Thomas E Markland, John D Chodera, Gianni De Fabritiis
NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. Journal of chemical information and modeling (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Pavan Kumar Behara, David L Dotson, Raimondas Galvelis, John E Herr, Joshua T Horton, Yuezhi Mao, John D Chodera, Benjamin P Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E Markland
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Scientific data 10 (1) (2023)
Peter Eastman, Raimondas Galvelis, Raul P Pelaez, Charlles R A Abreu, Stephen E Farr, Emilio Gallicchio, Anton Gorenko, Michael M Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A Mitchell, Vijay S Pande, João P G L M Rodrigues, Jaime Rodríguez-Guerra Pedregal, Andrew C Simmonett, Sukrit Singh, Jason Swails, Philip Turner, Yuanqing Wang, Ivy Zhang, John D Chodera, Gianni De Fabritiis, Thomas E Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. The journal of physical chemistry. B 128 (1) (2023)
Daniel G A Smith, Lori A Burns, Andrew C Simmonett, Robert M Parrish, Matthew C Schieber, Raimondas Galvelis, Peter Kraus, Holger Kruse, Roberto Di Remigio, Asem Alenaizan, Andrew M James, Susi Lehtola, Jonathon P Misiewicz, Maximilian Scheurer, Robert A Shaw, Jeffrey B Schriber, Yi Xie, Zachary L Glick, Dominic A Sirianni, Joseph Senan O'Brien, Jonathan M Waldrop, Ashutosh Kumar, Edward G Hohenstein, Benjamin P Pritchard, Bernard R Brooks, Henry F Schaefer, Alexander Yu Sokolov, Konrad Patkowski, A Eugene DePrince Iii, Uğur Bozkaya, Rollin A King, Francesco A Evangelista, Justin M Turney, T Daniel Crawford, C David Sherrill
Psi4 1.4: Open-source software for high-throughput quantum chemistry. The Journal of chemical physics 152 (18) (2020)
Raimondas Galvelis, Stefan Doerr, João M Damas, Matt J Harvey, Gianni De Fabritiis
A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning. Journal of chemical information and modeling 59 (8) (2019)
Raimondas Galvelis, Yuji Sugita
Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics. Journal of chemical theory and computation 13 (6) (2017)