Gianni De Fabritiis

70 papers A* 5Journal 64Unranked 1

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`	REINFORCE-ING Chemical Language Models for Drug Discovery. J. Chem. Inf. Model. Morgan C. Thomas, Albert Bou, José Carlos Gómez-Tamayo, Gary Tresadern, Mazen Ahmad, Gianni De Fabritiis
2025	J	`jnl`	REINFORCE-ING Chemical Language Models in Drug Design. CoRR Morgan C. Thomas, Albert Bou, 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
2025	J	`jnl`	Test-Time Training Scaling Laws for Chemical Exploration in Drug Design. J. Chem. Inf. Model. Morgan C. Thomas, Albert Bou, Gianni De Fabritiis
2025	J	`jnl`	Test-Time Training Scaling for Chemical Exploration in Drug Design. CoRR Morgan C. Thomas, Albert Bou, Gianni De Fabritiis
2024	J	`jnl`	ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery. J. Chem. Inf. Model. Albert Bou, Morgan C. Thomas, Sebastian Dittert, Carles Navarro, Maciej Majewski, Ye Wang, Shivam Patel, Gary Tresadern, Mazen Ahmad, Vincent Moens, Woody Sherman, Simone Sciabola, Gianni De Fabritiis
2024	J	`jnl`	ACEGEN: Reinforcement learning of generative chemical agents for drug discovery. CoRR Albert Bou, Morgan C. Thomas, Sebastian Dittert, Carles Navarro Ramírez, Maciej Majewski, Ye Wang, Shivam Patel, Gary Tresadern, Mazen Ahmad, Vincent Moens, Woody Sherman, Simone Sciabola, Gianni De Fabritiis
2024	J	`jnl`	AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics. CoRR Antonio Mirarchi, Raúl P. Peláez, Guillem Simeon, Gianni De Fabritiis
2024	A*	`conf`	BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO. NeurIPS Sebastian Dittert, Vincent Moens, Gianni De Fabritiis
2024	J	`jnl`	BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO. CoRR Sebastian Dittert, Vincent Moens, Gianni De Fabritiis
2024	J	`jnl`	Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. J. Chem. Inf. Model. Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D. Chodera, Thomas E. Markland, Gianni De Fabritiis
2024	J	`jnl`	Machine Learning Potentials: A Roadmap Toward Next-Generation Biomolecular Simulations. CoRR Gianni De Fabritiis
2024	J	`jnl`	On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction. CoRR Nikolai Schapin, Carles Navarro, Albert Bou, Gianni De Fabritiis
2024	J	`jnl`	On the Inclusion of Charge and Spin States in Cartesian Tensor Neural Network Potentials. CoRR Guillem Simeon, Antonio Mirarchi, Raúl P. Peláez, Raimondas Galvelis, 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`	PlayMolecule pKAce: Small Molecule Protonation through Equivariant Neural Networks. CoRR Nikolai Schapin, Maciej Majewski, Mariona Torrens-Fontanals, Gianni De Fabritiis
2024	J	`jnl`	PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models. J. Cheminformatics Morgan C. Thomas, Mazen Ahmad, Gary Tresadern, 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
2024	A*	`conf`	TorchRL: A data-driven decision-making library for PyTorch. ICLR Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens
2023	J	`jnl`	Binding-and-folding recognition of an intrinsically disordered protein using online learning molecular dynamics. CoRR Pablo Herrera-Nieto, Adrià Pérez, Gianni De Fabritiis
2023	J	`jnl`	Machine Learning Small Molecule Properties in Drug Discovery. CoRR Nikolai Schapin, Maciej Majewski, Alejandro Varela-Rial, Carlos Arroniz, 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
2023	J	`jnl`	OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. CoRR Peter K. Eastman, Raimondas Galvelis, Raúl P. Peláez, 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, Andrew C. Simmonett, Jason M. Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland
2023	A*	`conf`	TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials. NeurIPS Guillem Simeon, Gianni De Fabritiis
2023	J	`jnl`	TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials. CoRR Guillem Simeon, Gianni De Fabritiis
2023	J	`jnl`	Top-down machine learning of coarse-grained protein force-fields. CoRR Carles Navarro, Maciej Majewski, Gianni De Fabritiis
2023	J	`jnl`	TorchRL: A data-driven decision-making library for PyTorch. CoRR Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens
2023	J	`jnl`	Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series. J. Chem. Inf. Model. Francesc Sabanés Zariquiey, Adrià Pérez, Maciej Majewski, Emilio Gallicchio, Gianni De Fabritiis
2022	A*	`conf`	Equivariant Transformers for Neural Network based Molecular Potentials. ICLR Philipp Thölke, 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
2022	J	`jnl`	SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. CoRR Peter K. Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E. Markland
2022	J	`jnl`	TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials. CoRR Philipp Thölke, Gianni De Fabritiis
2021	A*	`conf`	Guided Exploration with Proximal Policy Optimization using a Single Demonstration. ICML Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
2020	J	`jnl`	Generative Models for Molecular Design. J. Chem. Inf. Model. Kenneth M. Merz Jr., Gianni De Fabritiis, Guo-Wei Wei
2020	J	`jnl`	Guided Exploration with Proximal Policy Optimization using a Single Demonstration. CoRR Gabriele Libardi, Gianni De Fabritiis
2020	J	`jnl`	JCIM Special Issue on Generative Models for Molecular Design. J. Chem. Inf. Model. Kenneth M. Merz Jr., Gianni De Fabritiis, Guo-Wei Wei
2020	J	`jnl`	NAPPO: Modular and scalable reinforcement learning in pytorch. CoRR Albert Bou, Gianni De Fabritiis
2020	J	`jnl`	PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations. J. Chem. Inf. Model. Gerard Martínez-Rosell, Silvia Lovera, Zara A. Sands, Gianni De Fabritiis
2020	J	`jnl`	SkeleDock: A Web Application for Scaffold Docking in PlayMolecule. J. Chem. Inf. Model. Alejandro Varela-Rial, Maciej Majewski, Alberto Cuzzolin, Gerard Martínez-Rosell, Gianni De Fabritiis
2020	J	`jnl`	Small Molecule Modulation of Intrinsically Disordered Proteins Using Molecular Dynamics Simulations. J. Chem. Inf. Model. Pablo Herrera-Nieto, Adrià Pérez, 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
2019	J	`jnl`	LigVoxel: inpainting binding pockets using 3D-convolutional neural networks. Bioinform. Miha Skalic, Alejandro Varela-Rial, José Jiménez, Gerard Martínez-Rosell, Gianni De Fabritiis
2019	J	`jnl`	PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks. J. Chem. Inf. Model. José Jiménez, Davide Sabbadin, Alberto Cuzzolin, Gerard Martínez-Rosell, Jacob Gora, John Manchester, José S. Duca, Gianni De Fabritiis
2019	J	`jnl`	PlayMolecule BindScope: large scale CNN-based virtual screening on the web. Bioinform. Miha Skalic, Gerard Martínez-Rosell, José Jiménez, Gianni De Fabritiis
2019	J	`jnl`	Shape-Based Generative Modeling for de Novo Drug Design. J. Chem. Inf. Model. Miha Skalic, José Jiménez, Davide Sabbadin, Gianni De Fabritiis
2018	J	`jnl`	KDEEP: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks. J. Chem. Inf. Model. José Jiménez, Miha Skalic, Gerard Martínez-Rosell, Gianni De Fabritiis
2018	J	`jnl`	Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors. J. Chem. Inf. Model. Gerard Martínez-Rosell, Matt J. Harvey, Gianni De Fabritiis
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
2017	J	`jnl`	PlayMolecule ProteinPrepare: A Web Application for Protein Preparation for Molecular Dynamics Simulations. J. Chem. Inf. Model. Gerard Martínez-Rosell, Toni Giorgino, Gianni De Fabritiis
2015	J	`jnl`	AceCloud: Molecular Dynamics Simulations in the Cloud. J. Chem. Inf. Model. Matt J. Harvey, Gianni De Fabritiis
2015	J	`jnl`	Insights from Fragment Hit Binding Assays by Molecular Simulations. J. Chem. Inf. Model. Noelia Ferruz, Matthew J. Harvey, Jordi Mestres, 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
2014	J	`jnl`	Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods. J. Chem. Inf. Model. Gianluigi Lauro, Noelia Ferruz, Simone Fulle, Matt J. Harvey, Paul W. Finn, Gianni De Fabritiis
2013	J	`jnl`	Computational Modeling of an Epidermal Growth Factor Receptor Single-Mutation Resistance to Cetuximab in Colorectal Cancer Treatment. J. Chem. Inf. Model. Ignasi Buch, Noelia Ferruz, Gianni De Fabritiis
2011	J	`jnl`	Swan: A tool for porting CUDA programs to OpenCL. Comput. Phys. Commun. Matt J. Harvey, Gianni De Fabritiis
2010	J	`jnl`	Distributed computing as a virtual supercomputer: Tools to run and manage large-scale BOINC simulations. Comput. Phys. Commun. Toni Giorgino, Matt J. Harvey, Gianni De Fabritiis
2010	J	`jnl`	High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing. J. Chem. Inf. Model. Ignasi Buch, Matt J. Harvey, Toni Giorgino, David P. Anderson, Gianni De Fabritiis
2010	J	`jnl`	Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors. PLoS Comput. Biol. Jana Selent, Ferran Sanz, Manuel Pastor, Gianni De Fabritiis
2010	J	`jnl`	Statistical Analysis of Global Connectivity and Activity Distributions in Cellular Networks. J. Comput. Biol. Adrián López García de Lomana, Qasim K. Beg, Gianni De Fabritiis, Jordi Villà-Freixa
2007	J	`jnl`	Performance of the Cell processor for biomolecular simulations. Comput. Phys. Commun. Gianni De Fabritiis
2006	J	`jnl`	A stochastic Trotter integration scheme for dissipative particle dynamics. Math. Comput. Simul. Mar Serrano, Gianni De Fabritiis, Pep Español, Peter V. Coveney
2006	J	`jnl`	Coupled applications on distributed resources. Comput. Phys. Commun. Peter V. Coveney, Gianni De Fabritiis, Matt J. Harvey, Stephen Pickles, Andrew R. Porter
1999	—	`conf`	Performance evaluation of a FD-TD parallel code for microwave ovens design. PARCO Giovanni Erbacci, Gianni De Fabritiis, Gaetano Bellanca, Paolo Bassi, R. Roccari