Stefan Doerr - RankMe

17 papers Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules. CoRR Stephen E. Farr, Stefan Doerr, Antonio Mirarchi, Francesc Sabanés Zariquiey, Gianni De Fabritiis
2025	J	`jnl`	QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials. CoRR Francesc Sabanés Zariquiey, Stephen E. Farr, Stefan Doerr, Gianni De Fabritiis
2025	J	`jnl`	QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials. J. Chem. Inf. Model. Francesc Sabanés Zariquiey, Stephen E. Farr, Stefan Doerr, Gianni De Fabritiis
2025	J	`jnl`	Speak to a Protein: An Interactive Multimodal Co-Scientist for Protein Analysis. CoRR Carles Navarro, Mariona Torrens, Philipp Thölke, Stefan Doerr, Gianni De Fabritiis
2024	J	`jnl`	PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data. J. Chem. Inf. Model. Mariona Torrens-Fontanals, Panagiotis Tourlas, Stefan Doerr, Gianni De Fabritiis
2024	J	`jnl`	TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. CoRR Raúl P. Peláez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter K. Eastman, Stefan Doerr, Philipp Thölke, Thomas E. Markland, Gianni De Fabritiis
2023	J	`jnl`	NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. J. Chem. Inf. Model. Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis
2022	J	`jnl`	Machine Learning Coarse-Grained Potentials of Protein Thermodynamics. CoRR Maciej Majewski, Adrià Pérez, Philipp Thölke, Stefan Doerr, Nicholas E. Charron, Toni Giorgino, Brooke E. Husic, Cecilia Clementi, Frank Noé, Gianni De Fabritiis
2022	J	`jnl`	NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics. CoRR Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis
2022	J	`jnl`	PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks. J. Chem. Inf. Model. Alejandro Varela-Rial, Iain Maryanow, Maciej Majewski, Stefan Doerr, Nikolai Schapin, José Jiménez-Luna, Gianni De Fabritiis
2020	J	`jnl`	TorchMD: A deep learning framework for molecular simulations. CoRR Stefan Doerr, Maciej Majewski, Adrià Pérez, Andreas Krämer, Cecilia Clementi, Frank Noé, Toni Giorgino, Gianni De Fabritiis
2019	J	`jnl`	A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning. J. Chem. Inf. Model. Raimondas Galvelis, Stefan Doerr, João M. Damas, Matt J. Harvey, Gianni De Fabritiis
2018	—	`—`	Applications of machine learning in molecular simulations: Transcending barriers. Stefan Doerr
2018	J	`jnl`	Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling. Int. J. Appl. Earth Obs. Geoinformation Francisco José Romero-Ramírez, Rafael M. Navarro-Cerrillo, M. Ángeles Varo-Martínez, Jose Luis Quero, Stefan Doerr, Rocío Hernández-Clemente
2017	J	`jnl`	DeepSite: protein-binding site predictor using 3D-convolutional neural networks. Bioinform. José Jiménez, Stefan Doerr, Gerard Martínez-Rosell, Alexander S. Rose, Gianni De Fabritiis
2017	J	`jnl`	Dimensionality reduction methods for molecular simulations. CoRR Stefan Doerr, Igor Ariz, Matthew J. Harvey, Gianni De Fabritiis
2014	J	`jnl`	Kinetic Characterization of Fragment Binding in AmpC β-Lactamase by High-Throughput Molecular Simulations. J. Chem. Inf. Model. Paola Bisignano, Stefan Doerr, Matt J. Harvey, Angelo D. Favia, Andrea Cavalli, Gianni De Fabritiis