{"total":64,"rows":[{"id":"2405.00781","title":"Barren Plateaus in Variational Quantum Computing","created":"2024-05-01","cited_by_count":133,"area":null},{"id":"2101.02464","title":"Information-theoretic bounds on quantum advantage in machine learning","created":"2021-01-07","cited_by_count":96,"area":null},{"id":"2101.10154","title":"Variational Neural Annealing","created":"2021-01-25","cited_by_count":47,"area":null},{"id":"2210.14894","title":"Learning to predict arbitrary quantum processes","created":"2022-10-26","cited_by_count":35,"area":null},{"id":"2110.04541","title":"The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design","created":"2021-10-09","cited_by_count":33,"area":null},{"id":"2208.12590","title":"Ab-initio quantum chemistry with neural-network wavefunctions","created":"2022-08-26","cited_by_count":29,"area":null},{"id":"2502.08696","title":"Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics","created":"2025-02-12","cited_by_count":29,"area":"diffusion"},{"id":"2112.10526","title":"NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems","created":"2021-12-20","cited_by_count":28,"area":null},{"id":"2103.10293","title":"Neural tensor contractions and the expressive power of deep neural quantum states","created":"2021-03-18","cited_by_count":21,"area":null},{"id":"2106.12974","title":"Tensor networks for unsupervised machine learning","created":"2021-06-24","cited_by_count":21,"area":null},{"id":"2109.12606","title":"Autoregressive neural-network wavefunctions for ab initio quantum chemistry","created":"2021-09-26","cited_by_count":21,"area":null},{"id":"2101.07243","title":"Gauge Invariant and Anyonic Symmetric Transformer and RNN Quantum States for Quantum Lattice Models","created":"2021-01-18","cited_by_count":18,"area":null},{"id":"2105.03928","title":"Which transformer architecture fits my data? A vocabulary bottleneck in self-attention","created":"2021-05-09","cited_by_count":16,"area":null},{"id":"2105.08086","title":"Neural Error Mitigation of Near-Term Quantum Simulations","created":"2021-05-17","cited_by_count":15,"area":null},{"id":"2110.06390","title":"Learning ground states of quantum Hamiltonians with graph networks","created":"2021-10-12","cited_by_count":12,"area":null},{"id":"2212.06835","title":"Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions","created":"2022-12-14","cited_by_count":10,"area":null},{"id":"2311.02143","title":"Pairing-based graph neural network for simulating quantum materials","created":"2023-11-03","cited_by_count":10,"area":null},{"id":"2509.04923","title":"Artificial intelligence for representing and characterizing quantum systems","created":"2025-09-05","cited_by_count":10,"area":null},{"id":"2108.02200","title":"Spacetime Neural Network for High Dimensional Quantum Dynamics","created":"2021-08-04","cited_by_count":9,"area":null},{"id":"2208.05637","title":"Scalable neural quantum states architecture for quantum chemistry","created":"2022-08-11","cited_by_count":9,"area":null},{"id":"2210.01169","title":"Neural-network solutions to stochastic reaction networks","created":"2022-09-29","cited_by_count":8,"area":null},{"id":"2302.08347","title":"The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems","created":"2023-02-16","cited_by_count":8,"area":null},{"id":"2304.01996","title":"ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation","created":"2023-04-04","cited_by_count":8,"area":null},{"id":"2306.16705","title":"NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry","created":"2023-06-29","cited_by_count":8,"area":null},{"id":"2206.07370","title":"Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems","created":"2022-06-15","cited_by_count":7,"area":null},{"id":"2304.04353","title":"Exponentially improved efficient machine learning for quantum many-body states with provable guarantees","created":"2023-04-10","cited_by_count":7,"area":null},{"id":"2404.07281","title":"Certifying almost all quantum states with few single-qubit measurements","created":"2024-04-10","cited_by_count":7,"area":null},{"id":"2405.07599","title":"Transferable Neural Wavefunctions for Solids","created":"2024-05-13","cited_by_count":7,"area":null},{"id":"2106.10558","title":"Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo","created":"2021-06-19","cited_by_count":6,"area":null},{"id":"2207.14314","title":"Supplementing Recurrent Neural Network Wave Functions with Symmetry and Annealing to Improve Accuracy","created":"2022-07-28","cited_by_count":6,"area":null},{"id":"2111.03383","title":"A Bayesian generative neural network framework for epidemic inference problems","created":"2021-11-05","cited_by_count":5,"area":null},{"id":"2405.17541","title":"Approximately-symmetric neural networks for quantum spin liquids","created":"2024-05-27","cited_by_count":5,"area":null},{"id":"2104.10696","title":"Scaling of neural-network quantum states for time evolution","created":"2021-04-21","cited_by_count":4,"area":null},{"id":"2302.12235","title":"Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows","created":"2023-02-23","cited_by_count":4,"area":null},{"id":"2307.01840","title":"Empirical Sample Complexity of Neural Network Mixed State Reconstruction","created":"2023-07-04","cited_by_count":4,"area":null},{"id":"2411.03900","title":"Retentive Neural Quantum States: Efficient Ans\\\"atze for Ab Initio Quantum Chemistry","created":"2024-11-06","cited_by_count":4,"area":null},{"id":"2211.02929","title":"Toward Neural Network Simulation of Variational Quantum Algorithms","created":"2022-11-05","cited_by_count":3,"area":null},{"id":"2311.01727","title":"Noise-Agnostic Quantum Error Mitigation with Data Augmented Neural Models","created":"2023-11-03","cited_by_count":3,"area":null},{"id":"2512.10309","title":"Tracking large chemical reaction networks and rare events by neural networks","created":"2025-12-11","cited_by_count":3,"area":null},{"id":"2605.13807","title":"Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo","created":"2026-05-13","cited_by_count":2,"area":null},{"id":"2203.14824","title":"Numerical and geometrical aspects of flow-based variational quantum Monte Carlo","created":"2022-03-28","cited_by_count":1,"area":null},{"id":"2211.14839","title":"Waveflow: boundary-conditioned normalizing flows applied to fermionic wavefunctions","created":"2022-11-27","cited_by_count":1,"area":null},{"id":"2212.11296","title":"Towards Neural Variational Monte Carlo That Scales Linearly with System Size","created":"2022-12-21","cited_by_count":1,"area":null},{"id":"2303.08162","title":"Artificial intelligence for artificial materials: moir\\'e atom","created":"2023-03-14","cited_by_count":1,"area":null},{"id":"2404.18840","title":"Fast Quantum Process Tomography via Riemannian Gradient Descent","created":"2024-04-29","cited_by_count":1,"area":null},{"id":"2509.12679","title":"Large Language Model Scaling Laws for Neural Quantum States in Quantum Chemistry","created":"2025-09-16","cited_by_count":1,"area":null},{"id":"2604.08661","title":"Geometry-Induced Long-Range Correlations in Recurrent Neural Network Quantum States","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2604.15768","title":"A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection with Neural Network Quantum States","created":"2026-04-17","cited_by_count":1,"area":null},{"id":"2606.13912","title":"Low-variance estimators overcome the phase-gradient bottleneck in complex-valued neural quantum states","created":"2026-06-11","cited_by_count":1,"area":null},{"id":"2607.01336","title":"Mechanistic Interpretability and Causal Feature Steering of Neural Quantum States via Sparse Autoencoders","created":"2026-07-01","cited_by_count":1,"area":"mechinterp"},{"id":"2106.08981","title":"Nonequilibrium thermodynamics of self-supervised learning","created":"2021-06-16","cited_by_count":0,"area":null},{"id":"2210.16493","title":"Neural network quantum state with proximal optimization: a ground-state searching scheme based on variational Monte Carlo","created":"2022-10-29","cited_by_count":0,"area":null},{"id":"2404.11093","title":"Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States","created":"2024-04-17","cited_by_count":0,"area":null},{"id":"2502.04271","title":"Variational decision diagrams for quantum-inspired machine learning applications","created":"2025-02-06","cited_by_count":0,"area":null},{"id":"2504.08141","title":"Variational quantum and neural quantum states algorithms for the linear complementarity problem","created":"2025-04-10","cited_by_count":0,"area":null},{"id":"2506.08594","title":"Solving excited states for long-range interacting trapped ions with neural networks","created":"2025-06-10","cited_by_count":0,"area":null},{"id":"2506.23550","title":"Seeding neural network quantum states with tensor network states","created":"2025-06-30","cited_by_count":0,"area":null},{"id":"2607.02292","title":"One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective","created":"2026-07-02","cited_by_count":0,"area":"deeprl"},{"id":"2607.18865","title":"Enhanced Neural Quantum State via Annealed Gradient Descent","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2609.22342","title":"Gradient-estimator design overcomes trainability barriers in neural-network-based variational optimization","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.27306","title":"Discrete Diffusion Models via Evolving Variational Autoregressive Networks","created":"2026-09-23","cited_by_count":0,"area":"diffusion"},{"id":"2609.33193","title":"Apparent Compression, Real Stability: The Intrinsic Dimension of Learning a Quantum Wavefunction","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.37733","title":"Foundation Neural-Network Quantum States for Molecular Potential Energy Surfaces in Second Quantization","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.00841","title":"Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}