Learning to Learn Visual Object Categories by Integrating Deep Learning with Hierarchical Bayes. - Andres Campero; Andrew Francl; Joshua B. Tenenbaum (CogSci, 2017)

A First Step in Combining Cognitive Event Features and Natural Language Representations to Predict Emotions. - Andres Campero; Bjarke Felbo; Joshua B. Tenenbaum; Rebecca Saxe (CoRR, 2017)

Logical Rule Induction and Theory Learning Using Neural Theorem Proving. - Andres Campero; Aldo Pareja; Tim Klinger; Josh Tenenbaum 001; Sebastian Riedel 001 (CoRR, 2018)

Learning with AMIGo: Adversarially Motivated Intrinsic Goals. - Andres Campero; Roberta Raileanu; Heinrich Küttler; Joshua B. Tenenbaum; Tim Rocktäschel; Edward Grefenstette (ICLR, 2021)

Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning. - Pedro A. Tsividis; João Loula; Jake Burga; Nathan Foss; Andres Campero; Thomas Pouncy; Samuel J. Gershman; Joshua B. Tenenbaum (CoRR, 2021)

A Test for Evaluating Performance in Human-Computer Systems. - Andres Campero; Michelle Vaccaro; Jaeyoon Song 001; Haoran Wen; Abdullah Almaatouq; Thomas W. Malone (CoRR, 2022)

Report on Candidate Computational Indicators for Conscious Valenced Experience. - Andres Campero (CoRR, 2024)