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The Variational Homoencoder: Learning to learn high capacity generative models from few examples.

, , , , and . UAI, page 988-997. AUAI Press, (2018)

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The Variational Homoencoder: Learning to learn high capacity generative models from few examples., , , , and . UAI, page 988-997. AUAI Press, (2018)A large-scale benchmark for few-shot program induction and synthesis., , , , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 175-186. PMLR, (2021)Communicating Natural Programs to Humans and Machines., , , , , , , , and . CoRR, (2021)DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning., , , , , , , , and . CoRR, (2020)Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning., , , and . NeurIPS, page 25192-25204. (2021)Implicit Representations of Meaning in Neural Language Models., , and . ACL/IJCNLP (1), page 1813-1827. Association for Computational Linguistics, (2021)Representing Partial Programs with Blended Abstract Semantics., , , , , and . ICLR, OpenReview.net, (2021)LARC: Language annotated Abstraction and Reasoning Corpus., , , , , and . CogSci, cognitivesciencesociety.org, (2021)Representing Partial Programs with Blended Abstract Semantics., , , , , and . CoRR, (2020)Show Your Work: Scratchpads for Intermediate Computation with Language Models., , , , , , , , , and 2 other author(s). CoRR, (2021)