Reconstructing quantum states with generative models. - Juan Carrasquilla; Giacomo Torlai; Roger G. Melko; Leandro Aolita (Nat. Mach. Intell., 2019)

Author Correction: Reconstructing quantum states with generative models. - Juan Carrasquilla; Giacomo Torlai; Roger G. Melko; Leandro Aolita (Nat. Mach. Intell., 2019)

Exploring entanglement and optimization within the Hamiltonian Variational Ansatz. - Roeland Wiersema; Cunlu Zhou; Yvette de Sereville; Juan Felipe Carrasquilla; Yong Baek Kim; Henry Yuen (CoRR, 2020)

Watch and learn - a generalized approach for transferrable learning in deep neural networks via physical principles. - Kyle Sprague; Juan Carrasquilla; Stephen Whitelam; Isaac Tamblyn (Mach. Learn. Sci. Technol., 2021)

Variational neural annealing. - Mohamed Hibat-Allah; Estelle M. Inack; Roeland Wiersema; Roger G. Melko; Juan Carrasquilla (Nat. Mach. Intell., 2021)

Supplementing Recurrent Neural Network Wave Functions with Symmetry and Annealing to Improve Accuracy. - Mohamed Hibat-Allah; Roger G. Melko; Juan Carrasquilla (CoRR, 2022)

Attention-based quantum tomography. - Peter Cha; Paul Ginsparg; Felix Wu; Juan Carrasquilla; Peter L. McMahon; Eun-Ah Kim (Mach. Learn. Sci. Technol., 2022)

Neural Error Mitigation of Near-Term Quantum Simulations. - Elizabeth R. Bennewitz; Florian Hopfmueller; Bohdan Kulchytskyy; Juan Carrasquilla; Pooya Ronagh (Nat. Mach. Intell., 2022)

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. - Kirill Neklyudov; Jannes Nys; Luca A. Thiede; Juan Carrasquilla; Qiang Liu; Max Welling; Alireza Makhzani (NeurIPS, 2023)

Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition. - Juan Carrasquilla; Mohamed Hibat-Allah; Estelle M. Inack; Alireza Makhzani; Kirill Neklyudov; Graham W. Taylor; Giacomo Torlai (CoRR, 2023)

Investigating Topological Order using Recurrent Neural Networks. - Mohamed Hibat-Allah; Roger G. Melko; Juan Carrasquilla (CoRR, 2023)

A Framework for Demonstrating Practical Quantum Advantage: Racing Quantum against Classical Generative Models. - Mohamed Hibat-Allah; Marta Mauri; Juan Carrasquilla; Alejandro Perdomo-Ortiz (CoRR, 2023)

Recurrent neural network wave functions for Rydberg atom arrays on kagome lattice. - Mohamed Hibat-Allah; Ejaaz Merali; Giacomo Torlai; Roger G. Melko; Juan Carrasquilla (CoRR, 2024)

Scalable quantum dynamics compilation via quantum machine learning. - Yuxuan Zhang; Roeland Wiersema; Juan Carrasquilla; Lukasz Cincio; Yong Baek Kim (CoRR, 2024)

Language models for quantum simulation. - Roger G. Melko; Juan Carrasquilla (Nat. Comput. Sci., 2024)

Here comes the SU(N): multivariate quantum gates and gradients. - Roeland Wiersema; Dylan Lewis; David Wierichs; Juan Carrasquilla; Nathan Killoran (Quantum, 2024)

Functional Neural Wavefunction Optimization. - Victor Armegioiu; Juan Carrasquilla; Siddhartha Mishra; Johannes Müller; Jannes Nys; Marius Zeinhofer; Hang Zhang (CoRR, 2025)