Guillermo Puebla
Cited by
Cited by
Human-like generalization in a machine through predicate learning
LAA Doumas, G Puebla, AE Martin
arXiv preprint arXiv:1806.01709, 2018
The relational processing limits of classic and contemporary neural network models of language processing
G Puebla, AE Martin, LAA Doumas
arXiv preprint arXiv:1905.05708, 2019
A theory of the detection and learning of structured representations of similarity and relative magnitude
LAA Doumas, A Hamer, G Puebla, AE Martin
The 39th annual conference of the cognitive science society (cogsci 2017 …, 2017
How we learn things we don’t know already: A theory of learning structured representations from experience
LAA Doumas, G Puebla, AE Martin
bioRxiv, 198804, 2017
Why Designer's intended function is central for proper function assignment and artifact conceptualization: Essentialist and Normative accounts
S Chaigneau, G Puebla, E Canessa
Developmental Review 41, 38-50, 2016
Inference and coherence in causal-based artifact categorization
G Puebla, SE Chaigneau
Cognition 130 (1), 50-65, 2014
The proper function of artifacts: intentions, conventions and causal inferences
SE Chaigneau, G Puebla
Review of Philosophy and Psychology 4 (3), 391-406, 2013
Relation learning in a neurocomputational architecture supports cross-domain transfer
LAA Doumas, G Puebla, AE Martin, JE Hummel
Proceedings of the 42nd Annual Conference of the Cognitive Science Society …, 2020
Is the Centrality of Design History Function an Effect of Causal Knowledge?
G Puebla-Ramírez, S Chaigneau
Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011
Can deep convolutional neural networks support relational reasoning in the same-different task?
G Puebla, JS Bowers
bioRxiv, 2021
Can Deep Convolutional Neural Networks Learn Same-Different Relations?
G Puebla, JS Bowers
bioRxiv, 2021
A Piecemeal Processing Strategy Model for Causal-Based Categorization
G Puebla, SE Chaigneau
Proceedings of the 41st Annual Meeting of the Cognitive Science Society, 2019
Predicate learning via neural oscillations supports one-shot generalization between video games
LAA Doumas, G Puebla, JE Hummel, AE Martin
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