An Evaluation of Auto-Scoping in OpenMP. - Michael Voss; Eric Chiu; Patrick Man Yan Chow; Catherine Wong; Kevin Yuen 001 (WOMPAT, 2004)

Challenges for Digital Literacy in English Curriculum. - Charles Lam; Catherine Wong (Teach4DH@GSCL, 2017)

Transfer Learning to Learn with Multitask Neural Model Search. - Catherine Wong; Andrea Gesmundo (CoRR, 2017)

DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation. - Catherine Wong (CoRR, 2017)

Transfer Learning with Neural AutoML. - Catherine Wong; Neil Houlsby; Yifeng Lu; Andrea Gesmundo (NeurIPS, 2018)

Transfer Automatic Machine Learning. - Catherine Wong; Neil Houlsby; Yifeng Lu; Andrea Gesmundo (CoRR, 2018)

Amanuensis: The Programmer's Apprentice. - Thomas Dean; Maurice Chiang; Marcus Gomez; Nate Gruver; Yousef Hindy; Michelle S. Lam; Peter Lu; Sophia Sanchez; Rohun Saxena; Michael Smith; Lucy Wang; Catherine Wong (CoRR, 2018)

Modeling Expertise with Neurally-Guided Bayesian Program Induction. - Catherine Wong; Kevin Ellis; Mathias Sablé-Meyer; Josh Tenenbaum 001 (CogSci, 2019)

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning. - Kevin Ellis; Catherine Wong; Maxwell I. Nye; Mathias Sablé-Meyer; Luc Cary; Lucas Morales; Luke B. Hewitt; Armando Solar-Lezama; Joshua B. Tenenbaum (CoRR, 2020)

LARC: Language annotated Abstraction and Reasoning Corpus. - Samuel Acquaviva; Yewen Pu; Maxwell I. Nye; Catherine Wong; Michael Henry Tessler; Josh Tenenbaum 001 (CogSci, 2021)

Core knowledge objects in reasoning and language use for highly abstract inductive tasks. - Gabrielle E. Ecanow; Catherine Wong; Samuel Acquaviva; Yewen Pu; Marta Kryven; Josh Tenenbaum 001 (CogSci, 2021)

Language as a bootstrap for compositional visual reasoning. - Catherine Wong; Yoni Friedman; Jacob Andreas; Josh Tenenbaum 001 (CogSci, 2021)

Leveraging Language to Learn Program Abstractions and Search Heuristics. - Catherine Wong; Kevin Ellis; Joshua B. Tenenbaum; Jacob Andreas (ICML, 2021)

DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning. - Kevin Ellis; Catherine Wong; Maxwell I. Nye; Mathias Sablé-Meyer; Lucas Morales; Luke B. Hewitt; Luc Cary; Armando Solar-Lezama; Joshua B. Tenenbaum (PLDI, 2021)

Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks. - Katherine M. Collins; Catherine Wong; Jiahai Feng; Megan Wei; Josh Tenenbaum 001 (CogSci, 2022)

Identifying concept libraries from language about object structure. - Catherine Wong; William P. McCarthy; Gabriel Grand; Yoni Friedman; Josh Tenenbaum 001; Jacob Andreas; Robert D. Hawkins; Judith E. Fan (CogSci, 2022)

Communicating Natural Programs to Humans and Machines. - Samuel Acquaviva; Yewen Pu; Marta Kryven; Theodoros Sechopoulos; Catherine Wong; Gabrielle E. Ecanow; Maxwell I. Nye; Michael Henry Tessler; Josh Tenenbaum 001 (NeurIPS, 2022)

Top-Down Synthesis for Library Learning. - Matthew Bowers; Theo X. Olausson; Catherine Wong; Gabriel Grand; Joshua B. Tenenbaum; Kevin Ellis; Armando Solar-Lezama (CoRR, 2022)

BASIN-3D: A brokering framework to integrate diverse environmental data. - Charuleka Varadharajan; Valerie C. Hendrix; Danielle S. Christianson; Madison Burrus; Catherine Wong; Susan S. Hubbard; Deborah A. Agarwal (Comput. Geosci., 2022)