Juan Carrasquilla

According to our database, Juan Carrasquilla authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Here comes the SU(N): multivariate quantum gates and gradients.

Roeland Wiersema, Dylan Lewis, David Wierichs, Juan Carrasquilla, Nathan Killoran

Quantum, March, 2024

Language models for quantum simulation.

Roger G. Melko, Juan Carrasquilla

Nat. Comput. Sci., 2024

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

Investigating Topological Order using Recurrent Neural Networks.

Mohamed Hibat-Allah, Roger G. Melko, Juan Carrasquilla

CoRR, 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

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation.

Kirill Neklyudov, Jannes Nys, Luca Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Neural Error Mitigation of Near-Term Quantum Simulations.

Elizabeth R. Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy, Juan Carrasquilla, Pooya Ronagh

Nat. Mach. Intell., 2022

Attention-based quantum tomography.

Peter Cha, Paul Ginsparg, Felix Wu, Juan Carrasquilla, Peter L. McMahon, Eun-Ah Kim

Mach. Learn. Sci. Technol., 2022

Supplementing Recurrent Neural Network Wave Functions with Symmetry and Annealing to Improve Accuracy.

Mohamed Hibat-Allah, Roger G. Melko, Juan Carrasquilla

CoRR, 2022

2021

Variational neural annealing.

Mohamed Hibat-Allah, Estelle M. Inack, Roeland Wiersema, Roger G. Melko, Juan Carrasquilla

Nat. Mach. Intell., 2021

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

2020

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

2019

Author Correction: Reconstructing quantum states with generative models.

Juan Carrasquilla, Giacomo Torlai, Roger G. Melko, Leandro Aolita

Nat. Mach. Intell., 2019

Reconstructing quantum states with generative models.

Juan Carrasquilla, Giacomo Torlai, Roger G. Melko, Leandro Aolita

Nat. Mach. Intell., 2019