Human-like generalization in a machine through predicate learning. - Leonidas A. A. Doumas; Guillermo Puebla; Andrea E. Martin (CoRR, 2018)

A Piecemeal Processing Strategy Model for Causal-Based Categorization. - Guillermo Puebla; Sergio E. Chaigneau (CogSci, 2019)

The relational processing limits of classic and contemporary neural network models of language processing. - Guillermo Puebla; Andrea E. Martin; Leonidas A. A. Doumas (CoRR, 2019)

Relation learning in a neurocomputational architecture supports cross-domain transfer. - Leonidas A. A. Doumas; Guillermo Puebla; Andrea E. Martin; John E. Hummel (CogSci, 2020)

Can Deep Convolutional Neural Networks Learn Same-Different Relations? - Guillermo Puebla; Jeffrey S. Bowers (CogSci, 2021)

Learning Relational Rules from Rewards. - Guillermo Puebla; Leonidas A. A. Doumas (CoRR, 2022)

The role of object-centric representations, guided attention, and external memory on generalizing visual relations. - Guillermo Puebla; Jeffrey S. Bowers (CoRR, 2023)

On the importance of severely testing deep learning models of cognition. - Jeffrey S. Bowers; Gaurav Malhotra; Federico Adolfi; Marin Dujmovic; Milton Llera Montero; Valerio Biscione; Guillermo Puebla; John E. Hummel; Rachel F. Heaton (Cogn. Syst. Res., 2023)

MindSet: Vision. A toolbox for testing DNNs on key psychological experiments. - Valerio Biscione; Dong Yin; Gaurav Malhotra; Marin Dujmovic; Milton Llera Montero; Guillermo Puebla; Federico Adolfi; Rachel F. Heaton; John E. Hummel; Benjamin D. Evans; Karim Habashy; Jeffrey S. Bowers (CoRR, 2024)

Visual reasoning in object-centric deep neural networks: A comparative cognition approach. - Guillermo Puebla; Jeffrey S. Bowers (Neural Networks, 2025)