| Modern applications of machine learning in quantum sciences A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ... arXiv preprint arXiv:2204.04198, 2022 | 57* | 2022 |
| Interpretable and unsupervised phase classification J Arnold, F Schäfer, M Žonda, AUJ Lode Physical Review Research 3 (3), 033052, 2021 | 32 | 2021 |
| Replacing neural networks by optimal analytical predictors for the detection of phase transitions J Arnold, F Schäfer Physical Review X 12 (3), 031044, 2022 | 15 | 2022 |
| Machine learning product state distributions from initial reactant states for a reactive atom–diatom collision system J Arnold, JC San Vicente Veliz, D Koner, N Singh, RJ Bemish, M Meuwly The Journal of Chemical Physics 156 (3), 2022 | 13 | 2022 |
| Machine Learning for Observables: Reactant to Product State Distributions for Atom–Diatom Collisions J Arnold, D Koner, S Käser, N Singh, RJ Bemish, M Meuwly The Journal of Physical Chemistry A 124 (35), 7177-7190, 2020 | 13 | 2020 |
| Performance Bounds for Quantum Control F Holtorf, F Schäfer, J Arnold, C Rackauckas, A Edelman arXiv preprint arXiv:2304.03366, 2023 | 2 | 2023 |
| Combining Machine Learning and Spectroscopy to Model Reactive Atom+ Diatom Collisions JC San Vicente Veliz, J Arnold, RJ Bemish, M Meuwly The Journal of Physical Chemistry A 126 (43), 7971-7980, 2022 | 2 | 2022 |
| Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion J Arnold, F Schäfer, N Lörch arXiv preprint arXiv:2311.09128, 2023 | 1 | 2023 |
| Mapping out phase diagrams with generative classifiers J Arnold, F Schäfer, A Edelman, C Bruder arXiv preprint arXiv:2306.14894, 2023 | 1 | 2023 |
| Sum-of-Squares Bounds for Quantum Optimal Control F Holtorf, F Schäfer, J Arnold, C Rackauckas, A Edelman 2023 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2023 | | 2023 |
| Machine learning phase transitions: Connections to the Fisher information J Arnold, N Lörch, F Holtorf, F Schäfer arXiv preprint arXiv:2311.10710, 2023 | | 2023 |
| How deep neural networks learn thermal phase transitions J Arnold, F Schäfer APS March Meeting Abstracts 2023, Q53. 002, 2023 | | 2023 |
| Revealing phase diagrams of quantum systems with optimal predictors J Arnold, F Schäfer APS March Meeting Abstracts 2023, S62. 002, 2023 | | 2023 |
| Entropy production in ticking clocks J Arnold Institute for Theoretical Physics, ETH Zurich, 2021 | | 2021 |
| Quantum simulators, phase transitions, resonant tunneling, and variances: A many-body perspective AUJ Lode, OE Alon, J Arnold, A Bhowmik, M Büttner, LS Cederbaum, ... International Conference on High Performance Computing in Science and …, 2021 | | 2021 |
| Interpretable and unsupervised phase classification based on averaged input features J Arnold, F Schäfer, M Zonda, A Lode APS March Meeting Abstracts 2021, L21. 002, 2021 | | 2021 |
Frank SchäferMassachusetts Institute of TechnologyVerified email at mit.edu
