Backflow Transformations via Neural Networks for Quantum Many-Body Wave Functions D Luo, BK Clark Physical Review Letters 122 (22), 226401, 2019 | 148 | 2019 |

Deep Learning Enabled Strain Mapping of Single-Atom Defects in Two-Dimensional Transition Metal Dichalcogenides with Sub-Picometer Precision CH Lee, A Khan, D Luo, TP Santos, C Shi, BE Janicek, S Kang, W Zhu, ... Nano Letters 20 (5), 3369-3377, 2020 | 99 | 2020 |

Autoregressive Transformer Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation D Luo, Z Chen, J Carrasquilla, BK Clark Physical review letters 128 (9), 090501, 2022 | 72 | 2022 |

Classical shadows for quantum process tomography on near-term quantum computers R Levy, D Luo, BK Clark Physical Review Research 6 (1), 013029, 2024 | 58 | 2024 |

Probabilistic simulation of quantum circuits with the Transformer J Carrasquilla, D Luo, F Pérez, A Milsted, BK Clark, M Volkovs, L Aolita Physical Review A 104 (3), 032610, 2021 | 55* | 2021 |

Framework for simulating gauge theories with dipolar spin systems D Luo, J Shen, M Highman, BK Clark, B DeMarco, AX El-Khadra, ... Physical Review A 102 (3), 032617, 2020 | 53* | 2020 |

Gauge equivariant neural networks for quantum lattice gauge theories D Luo, G Carleo, BK Clark, J Stokes Physical Review Letters 127 (27), 276402, 2021 | 48 | 2021 |

Protocol Discovery for the Quantum Control of Majoranas by Differentiable Programming and Natural Evolution Strategies L Coopmans, D Luo, G Kells, BK Clark, J Carrasquilla PRX Quantum 2 (2), 020332, 2021 | 39 | 2021 |

Gauge Invariant and Anyonic Symmetric Transformer and RNN Quantum States for Quantum Lattice Models D Luo, Z Chen, K Hu, Z Zhao, VM Hur, BK Clark Physical Review Research 5 (1), 013216, 2023 | 30* | 2023 |

Beyond many-body localized states in a spin-disordered Hubbard model X Yu, D Luo, BK Clark Physical Review B 98 (11), 115106, 2018 | 19 | 2018 |

Gauge Equivariant Neural Networks for 2+ 1D U (1) Gauge Theory Simulations in Hamiltonian Formulation D Luo, S Yuan, J Stokes, BK Clark NeurIPS 2022 AI for Science Workshop, 2022 | 15 | 2022 |

ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation Z Chen, L Newhouse, E Chen, D Luo, M Soljacic Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 12* | 2023 |

Simulating 2+ 1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions Z Chen, D Luo, K Hu, BK Clark arXiv preprint arXiv:2212.06835, 2022 | 12 | 2022 |

Finite-volume pionless effective field theory for few-nucleon systems with differentiable programming X Sun, W Detmold, D Luo, PE Shanahan Physical Review D 105 (7), 074508, 2022 | 11 | 2022 |

Spacetime Neural Network for High Dimensional Quantum Dynamics J Wang, Z Chen, D Luo, Z Zhao, VM Hur, BK Clark 38th International Conference on Machine Learning Workshop on ”Beyond first …, 2021 | 11 | 2021 |

Variational Neural-Network Ansatz for Continuum Quantum Field Theory JM Martyn, K Najafi, D Luo Physical Review Letters 131 (8), 081601, 2023 | 10 | 2023 |

QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning D Luo, J Shen, R Dangovski, M Soljacic Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 9* | 2023 |

GenPhys: From Physical Processes to Generative Models Z Liu, D Luo, Y Xu, T Jaakkola, M Tegmark arXiv preprint arXiv:2304.02637, 2023 | 9 | 2023 |

Simulating quantum mechanics with a -term and an ’t Hooft anomaly on a synthetic dimension J Shen, D Luo, C Huang, BK Clark, AX El-Khadra, B Gadway, P Draper Physical Review D 105 (7), 074505, 2022 | 8 | 2022 |

Infinite Neural Network Quantum States: Entanglement and Training Dynamics D Luo, J Halverson Machine Learning: Science and Technology, 2023 | 7* | 2023 |