Loss-of-entanglement prediction of a controlled-PHASE gate in the framework of steepest-entropy-ascent quantum thermodynamics. - J. A. Montañez-Barrera; Cesar Damian-Ascencio; Michael R. von Spakovsky; Sergio Cano-Andrade (CoRR, 2020)

Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels. - J. A. Montañez-Barrera; Juan Manuel Barroso-Maldonado; A. F. Bedoya-Santacruz; Adrian Mota-Babiloni (CoRR, 2022)

Method for generating randomly perturbed density operators subject to different sets of constraints. - J. A. Montañez-Barrera; R. T. Holladay; G. P. Beretta; Michael R. von Spakovsky (Quantum Inf. Process., 2022)

Improving Performance in Combinatorial Optimization Problems with Inequality Constraints: An Evaluation of the Unbalanced Penalization Method on D-Wave Advantage. - J. A. Montañez-Barrera; Pim van den Heuvel; Dennis Willsch; Kristel Michielsen (QCE, 2023)

Transfer learning of optimal QAOA parameters in combinatorial optimization. - J. A. Montañez-Barrera; Dennis Willsch; Kristel Michielsen (Quantum Inf. Process., 2025)