| Restricted Boltzmann machines for quantum states with non-Abelian or anyonic symmetries T Vieijra, C Casert, J Nys, W De Neve, J Haegeman, J Ryckebusch, ... Physical review letters 124 (9), 097201, 2020 | 95* | 2020 |
| Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system C Casert, T Vieijra, J Nys, J Ryckebusch Physical Review E 99 (2), 023304, 2019 | 46 | 2019 |
| Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz C Casert, T Vieijra, S Whitelam, I Tamblyn Physical review letters 127 (12), 120602, 2021 | 23 | 2021 |
| Many-Body Quantum States with Exact Conservation of Non-Abelian and Lattice Symmetries through Variational Monte Carlo T Vieijra, J Nys Physical Review B 104 (4), 045123, 2021 | 21 | 2021 |
| Isospin composition of the high-momentum fluctuations in nuclei from asymptotic momentum distributions J Ryckebusch, W Cosyn, T Vieijra, C Casert Physical Review C 100 (5), 054620, 2019 | 20 | 2019 |
| Direct sampling of projected entangled-pair states T Vieijra, J Haegeman, F Verstraete, L Vanderstraeten Physical Review B 104 (23), 235141, 2021 | 15 | 2021 |
| Generative modeling with projected entangled-pair states T Vieijra, L Vanderstraeten, F Verstraete arXiv preprint arXiv:2202.08177, 2022 | 13 | 2022 |
| Optical lattice experiments at unobserved conditions with generative adversarial deep learning C Casert, K Mills, T Vieijra, J Ryckebusch, I Tamblyn Physical Review Research 3 (3), 033267, 2021 | 11 | 2021 |
| Artificial neural networks and tensor networks in Variational Monte Carlo T Vieijra Ghent University, 2022 | | 2022 |
| Towards neural network quantum states with nonabelian symmetries T Vieijra, C Casert, J Nys, W De Neve, J Haegeman, J Ryckebusch, ... Bulletin of the American Physical Society 65, 2020 | | 2020 |
| Adversarial machine learning for modeling the distribution of large-scale ultracold atom experiments C Casert, K Mills, T Vieijra, J Ryckebusch, I Tamblyn Bulletin of the American Physical Society 65, 2020 | | 2020 |
| Discriminative and generative machine learning for spin systems based on physically interpretable features C Casert, K Mills, J Nys, J Ryckebusch, I Tamblyn, T Vieijra StatPhys 27 Main Conference, 2019 | | 2019 |
| Dynamical large deviations of kinetically constrained models using neural-network states C Casert, T Vieijra, S Whitelam, I Tamblyn | | |
| Large deviations of one-dimensional kinetically constrained models with recurrent neural networks C Casert, T Vieijra, S Whitelam, I Tamblyn | | |
Corneel CasertLawrence Berkeley National LaboratoryVerified email at lbl.gov
