24 citations · 53 across the 6 of their papers we have counts for
6 papers
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition Approach
Guillermo Puebla, Jeffrey S. Bowers
Achieving visual reasoning is a long-term goal of artificial intelligence. In the last decade, several studies have applied deep neural networks (DNNs) to the task of learning visu…
The role of object-centric representations, guided attention, and external memory on generalizing visual relations
Guillermo Puebla, Jeffrey S. Bowers
Visual reasoning is a long-term goal of vision research. In the last decade, several works have attempted to apply deep neural networks (DNNs) to the task of learning visual relati…
Learning Rules from Rewards
Guillermo Puebla, Leonidas A. A. Doumas
Humans can flexibly generalize knowledge across domains by leveraging structured relational representations. While prior research has shown how such representations support analogi…
A Theory of Relation Learning and Cross-domain Generalization
Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin +1
People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in…
The relational processing limits of classic and contemporary neural network models of language processing
Guillermo Puebla, Andrea E. Martin, Leonidas A. A. Doumas
The ability of neural networks to capture relational knowledge is a matter of long-standing controversy. Recently, some researchers in the PDP side of the debate have argued that (…
Human-like generalization in a machine through predicate learning
Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin
Humans readily generalize, applying prior knowledge to novel situations and stimuli. Advances in machine learning and artificial intelligence have begun to approximate and even sur…