Improving the Quality of Quantum Services Generation Process: Controlling Errors and Noise. - Jaime Alvarado-Valiente; Javier Romero-Álvarez; Danel Arias; Erik B. Terres; José García-Alonso; Enrique Moguel; Pablo García Bringas; Juan Manuel Murillo (HAIS, 2023)

Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis. - Erik Terres Escudero; Danel Arias Alamo; Oier Mentxaka Gómez; Pablo García Bringas (HAIS, 2023)

Let's do it right the first time: Survey on security concerns in the way to quantum software engineering. - Danel Arias; Ignacio García Rodríguez de Guzmán; Moisés Rodríguez 001; Erik B. Terres; Borja Sanz 001; José Gaviria de la Puerta; Iker Pastor; Agustín Zubillaga; Pablo García Bringas (Neurocomputing, 2023)

Quantum Services Engineering: development, quality, testing, and security (Q-SERV Project). - Enrique Moguel; José García-Alonso; Erik B. Terres-Escudero; Danel Arias; Pablo García Bringas; Ana Díaz-Muñoz; Moisés Rodríguez 001; Jesús Ramon Oviedo; Juan Manuel Murillo (CIbSE, 2024)

A Contrastive Symmetric Forward-Forward Algorithm (SFFA) for Continual Learning Tasks. - Erik B. Terres-Escudero; Javier Del Ser; Pablo García Bringas (CoLLAs, 2024)

On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization. - Erik B. Terres-Escudero; Javier Del Ser; Pablo García Bringas (ECAI, 2024)

Machine Learning Methods as Robust Quantum Noise Estimators. - Jon Gardeazabal-Gutierrez; Erik B. Terres-Escudero; Pablo García Bringas (HAIS (1), 2024)

Emerging NeoHebbian Dynamics in Forward-Forward Learning: Implications for Neuromorphic Computing. - Erik B. Terres-Escudero; Javier Del Ser; Pablo García Bringas (CoRR, 2024)

On the Robustness of Fully-Spiking Neural Networks in Open-World Scenarios using Forward-Only Learning Algorithms. - Erik B. Terres-Escudero; Javier Del Ser; Aitor Martínez-Seras; Pablo García Bringas (CoRR, 2024)