| Zero-field nuclear magnetic resonance of chemically exchanging systems DA Barskiy, MCD Tayler, I Marco-Rius, J Kurhanewicz, DB Vigneron, ... Nature communications 10 (1), 3002, 2019 | 57 | 2019 |
| Time-dependent variational principle for open quantum systems with artificial neural networks M Reh, M Schmitt, M Gärttner Physical Review Letters 127 (23), 230501, 2021 | 53 | 2021 |
| Efficient quantum state tomography with convolutional neural networks T Schmale, M Reh, M Gärttner npj Quantum Information 8 (1), 115, 2022 | 25 | 2022 |
| Optimizing design choices for neural quantum states M Reh, M Schmitt, M Gärttner Physical Review B 107 (19), 195115, 2023 | 22 | 2023 |
| jVMC: Versatile and performant variational Monte Carlo leveraging automated differentiation and GPU acceleration M Schmitt, M Reh SciPost Physics Codebases, 002, 2022 | 8 | 2022 |
| Variational Monte Carlo approach to partial differential equations with neural networks M Reh, M Gärttner Machine Learning: Science and Technology 3 (4), 04LT02, 2022 | 7 | 2022 |
| Zero-Field J-spectroscopy of Quadrupolar Nuclei R Picazo-Frutos, KF Sheberstov, JW Blanchard, E Van Dyke, M Reh, ... arXiv preprint arXiv:2011.05618, 2020 | 4 | 2020 |
| Sample-efficient estimation of entanglement entropy through supervised learning M Rieger, M Reh, M Gärttner Physical Review A 109 (1), 012403, 2024 | 1 | 2024 |
| Codebase release 0.1 for jVMC M Schmitt, M Reh SciPost Physics Codebases, 002, 2022 | | 2022 |
| A Neural-Network approach to the simulation of Open Quantum Dynamics using POVMs M Reh, M Gaerttner, M Schmitt APS March Meeting Abstracts 2021, A21. 006, 2021 | | 2021 |
Martin GärttnerProfessor of Physics, Friedrich Schiller University Jena, GermanyVerified email at uni-jena.de
