Quantum Machine Learning without Measurements. - Unai Alvarez-Rodriguez; Lucas Lamata; Pablo Escandell-Montero; José David Martín-Guerrero; Enrique Solano (CoRR, 2016)

Basic protocols in quantum reinforcement learning with superconducting circuits. - Lucas Lamata (CoRR, 2017)

Quantum Autoencoders via Quantum Adders with Genetic Algorithms. - Lucas Lamata; Unai Alvarez-Rodriguez; José David Martín-Guerrero; Mikel Sanz; Enrique Solano (CoRR, 2017)

Quantum Memristors in Quantum Photonics. - Mikel Sanz; Lucas Lamata; Enrique Solano (CoRR, 2017)

Generalized Quantum Reinforcement Learning with Quantum Technologies. - Francisco A. Cárdenas-López; Lucas Lamata; Juan Carlos Retamal; Enrique Solano (CoRR, 2017)

Quantum Artificial Life in an IBM Quantum Computer. - Unai Alvarez-Rodriguez; Mikel Sanz; Lucas Lamata; Enrique Solano (CoRR, 2017)

Measurement-based adaptation protocol with quantum reinforcement learning. - Francisco Albarrán-Arriagada; Juan Carlos Retamal; Enrique Solano; Lucas Lamata (CoRR, 2018)

Quantum computing cryptography: Unveiling cryptographic Boolean functions with quantum annealing. - Feng Hu; Lucas Lamata; Mikel Sanz; Xi Chen; Xingyuan Chen; Chao Wang; Enrique Solano (CoRR, 2018)

Experimental Implementation of a Quantum Autoencoder via Quantum Adders. - Yongcheng Ding; Lucas Lamata; Mikel Sanz; Xi Chen 059; Enrique Solano (CoRR, 2018)

Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computer. - J. Olivares-Sánchez; J. Casanova; Enrique Solano; Lucas Lamata (CoRR, 2018)

Parity-Assisted Generation of Nonclassical States of Light in Circuit Quantum Electrodynamics. - Francisco A. Cárdenas-López; Guillermo Romero; Lucas Lamata; Enrique Solano; Juan Carlos Retamal (Symmetry, 2019)

Symmetry in Quantum Optics Models. - Lucas Lamata (Symmetry, 2019)

Quantum Machine Learning. - José David Martín-Guerrero; Lucas Lamata (ESANN, 2020)

Quantum Teleportation for Control of Dynamic Systems and Autonomy. - Farbod Khoshnoud; Lucas Lamata; Clarence W. de Silva; Marco B. Quadrelli (CoRR, 2020)

Reinforcement learning for semi-autonomous approximate quantum eigensolver. - Francisco Albarrán-Arriagada; Juan Carlos Retamal; Enrique Solano; Lucas Lamata (Mach. Learn. Sci. Technol., 2020)

Quantum machine learning and quantum biomimetics: A perspective. - Lucas Lamata (Mach. Learn. Sci. Technol., 2020)

Quantum teleportation for control of dynamical Systems and Autonomy. - Farbod Khoshnoud; Lucas Lamata; Clarence W. de Silva; Marco B. Quadrelli (Mechatron. Syst. Control., 2021)

Implementation of a Hybrid Classical-Quantum Annealing Algorithm for Logistic Network Design. - Yongcheng Ding; Xi Chen 059; Lucas Lamata; Enrique Solano; Mikel Sanz (SN Comput. Sci., 2021)

Quantum Machine Learning: A tutorial. - José David Martín-Guerrero; Lucas Lamata (Neurocomputing, 2022)

An Approach to Interfacing the Brain with Quantum Computers: Practical Steps and Caveats. - Eduardo R. Miranda; Satvik Venkatesh; José D. Martín-Guerrero; Carlos Hernani-Morales; Lucas Lamata; Enrique Solano (Int. J. Unconv. Comput., 2022)

Quantum Artificial Intelligence: A tutorial. - José D. Martín-Guerrero; Lucas Lamata; Thomas Villmann (ESANN, 2023)

Quantum Machine Learning Implementations: Proposals and Experiments. - Lucas Lamata (CoRR, 2023)

Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer. - Yongcheng Ding; Javier Gonzalez-Conde; Lucas Lamata; José D. Martín-Guerrero; Enrique Lizaso; Samuel Mugel; Xi Chen 059; Román Orús; Enrique Solano; Mikel Sanz (Entropy, 2023)

A digital-analog quantum genetic algorithm using Rydberg atom arrays. - Aleix Llenas; Lucas Lamata (CoRR, 2024)

Digital-Analog Quantum Machine Learning. - Lucas Lamata (CoRR, 2024)

Quantum memristors for neuromorphic quantum machine learning. - Lucas Lamata (CoRR, 2024)