| Artificial intelligence applied to battery research: hype or reality? T Lombardo, M Duquesnoy, H El-Bouysidy, F Årén, A Gallo-Bueno, ... Chemical Reviews 122 (12), 10899-10969, 2021 | 287 | 2021 |
| Deep learning spectroscopy: Neural networks for molecular excitation spectra K Ghosh, A Stuke, M Todorović, PB Jørgensen, MN Schmidt, A Vehtari, ... Advanced science 6 (9), 1801367, 2019 | 248 | 2019 |
| Machine learning-based screening of complex molecules for polymer solar cells PB Jørgensen, M Mesta, S Shil, JM García Lastra, KW Jacobsen, ... The Journal of chemical physics 148 (24), 2018 | 120 | 2018 |
| A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning A Bhowmik, IE Castelli, JM Garcia-Lastra, PB Jørgensen, O Winther, ... Energy Storage Materials 21, 446-456, 2019 | 112 | 2019 |
| Neural message passing with edge updates for predicting properties of molecules and materials PB Jørgensen, KW Jacobsen, MN Schmidt arXiv preprint arXiv:1806.03146, 2018 | 108 | 2018 |
| Deep generative models for molecular science PB Jørgensen, MN Schmidt, O Winther Molecular informatics 37 (1-2), 1700133, 2018 | 92 | 2018 |
| Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks J Busk, PB Jørgensen, A Bhowmik, MN Schmidt, O Winther, T Vegge Machine Learning: Science and Technology 3 (1), 015012, 2021 | 53 | 2021 |
| Brokering between tenants for an international materials acceleration platform M Vogler, J Busk, H Hajiyani, PB Jørgensen, N Safaei, IE Castelli, ... Matter 6 (9), 2647-2665, 2023 | 24 | 2023 |
| DeepDFT: Neural Message Passing Network for Accurate Charge Density Prediction PB Jørgensen, A Bhowmik arXiv preprint arXiv:2011.03346, 2020 | 24 | 2020 |
| NeuralNEB—Neural Networks can find reaction paths fast M Schreiner, A Bhowmik, T Vegge, PB Jørgensen, O Winther Machine Learning: Science and Technology 3 (4), 045022, 2022 | 23 | 2022 |
| Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids PB Jørgensen, A Bhowmik npj Computational Materials 8 (1), 183, 2022 | 21 | 2022 |
| On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors JH Chang, PB Jørgensen, S Loftager, A Bhowmik, JMG Lastra, T Vegge Electrochimica Acta 388, 138551, 2021 | 16 | 2021 |
| An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation TL Hansen, PB Jørgensen, MA Badiu, BH Fleury IEEE Transactions on Signal Processing, 2018 | 16 | 2018 |
| Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors PB Jørgensen, EG del Río, MN Schmidt, KW Jacobsen arXiv preprint arXiv:1905.06048, 2019 | 15 | 2019 |
| Machine learning: deep learning spectroscopy: neural networks for molecular excitation spectra (adv. Sci. 9/2019) K Ghosh, A Stuke, M Todorović, PB Jørgensen, MN Schmidt, A Vehtari, ... Advanced Science 6 (9), 2019 | 14 | 2019 |
| Implementation of LTE SC-FDMA on the USRP2 software defined radio platform PB Jørgensen, TL Hansen, TB Sørensen, G Berardinelli 2011 IEEE Swedish Communication Technologies Workshop (Swe-CTW), 34-39, 2011 | 12 | 2011 |
| Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes BH Sjølin, PB Jørgensen, A Fedrigucci, T Vegge, A Bhowmik, IE Castelli Batteries & Supercaps 6 (6), e202300041, 2023 | 11 | 2023 |
| Bayesian Compressed Sensing with Unknown Measurement Noise Level TL Hansen, PB Jørgensen, NL Pedersen, CN Manchón, BH Fleury | 10* | |
| Joint sparse channel estimation and decoding: Continuous and discrete domain sparsity TL Hansen, PB Jørgensen, MA Badiu, BH Fleury CoRR, vol. abs/1507.02954, 2015 | 7 | 2015 |
| Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces J Busk, M Schmidt, O Winther, T Vegge, PB Jørgensen Physical Chemistry Chemical Physics, 2023 | 6 | 2023 |
