Peter Bjørn Jørgensen

Technical University of Denmark — Denmark

Materials Science · Physical Sciences

14h-index1.4kcitations43works1.02yr avg
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Research Topics

Machine Learning in Materials Science(32), Computational Drug Discovery Methods(18), Electron and X-Ray Spectroscopy Techniques(6), Advanced Wireless Communication Techniques(4), Sparse and Compressive Sensing Techniques(4)

Publications43 total

Graph2Mat: universal graph to matrix conversion for electron density prediction
Machine Learning Science and Technology·2025· 3 citedOpen Access
Graph2Mat: Universal graph to matrix conversion for electron density prediction
2025Open Access
GRAPH2MAT: UNIVERSAL GRAPH TO MATRIX CONVERSION FOR ELECTRON DENSITY PREDICTION
2024Open Access
Coherent energy and force uncertainty in deep learning force fields
arXiv (Cornell University)·2023· 8 citedOpen Access
Nanosecond MD of battery cathode materials with electron density description
Energy storage materials·2023· 5 citedOpen Access
Materials Funnel 2.0 - Data-driven hierarchical search for exploration of vast chemical spaces
2023· 1 citedOpen Access
Brokering between tenants for an international materials acceleration platform
Matter·2023· 36 citedOpen Access
Introducing Materials Funnel 2.0 - hierarchical search ininfinite chemical space
2023Open Access
Nanosecond MD of battery cathode materials withelectron density description
2023· 2 citedOpen Access
Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes
Batteries & Supercaps·2023· 5 citedOpen Access
Cover Picture: (Batteries & Supercaps 6/2023)
Batteries & Supercaps·2023Open Access
Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces
arXiv (Cornell University)·2023· 1 citedOpen Access
Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes
Batteries & Supercaps·2023· 14 citedOpen Access
Materials funnel 2.0 – data-driven hierarchical search for exploration of vast chemical spaces
Journal of Materials Chemistry A·2023· 1 cited
Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces
Physical Chemistry Chemical Physics·2023· 12 citedOpen Access
NeuralNEB—neural networks can find reaction paths fast
Machine Learning Science and Technology·2022· 36 citedOpen Access
Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT
Journal of Chemical Information and Modeling·2022· 3 cited
Brokering between tenants for an international materials acceleration platform
2022· 5 citedOpen Access
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids
npj Computational Materials·2022· 51 citedOpen Access
NeuralNEB -- Neural Networks can find Reaction Paths Fast
arXiv (Cornell University)·2022· 1 citedOpen Access
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Frequent Co-authors

Arghya Bhowmik(26), Tejs Vegge(14), Mikkel N. Schmidt(12), Ole Winther(9), Jonas Busk(9), Ivano E. Castelli(6), Thomas Hansen(6), J. M. García‐Lastra(5), Karsten W. Jacobsen(4), Bernard H. Fleury(4), Mihai-Alin Badiu(3), Benjamin Heckscher Sjølin(3), Andrea Fedrigucci(3), Pol Febrer(3), Miguel Pruneda(3), Pablo Ordejón(3), Raul Ortega Ochoa(3), Bardi Benediktsson(3), Kunal Ghosh(2), Annika Stuke(2)