Marc Brockschmidt
4 papers in the PaperMetrix corpus
Papers by this author
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Summary - TerpreT: A Probabilistic Programming Language for Program Induction
2016 · arXiv (Cornell University)
We study machine learning formulations of inductive program synthesis; that is, given input-output examples, synthesize source code that maps inputs to corresponding outputs. Our key contribution is TerpreT, a domain-specific language for expressing program synthesis …
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Differentiable Programs with Neural Libraries
2016 · arXiv (Cornell University)
We develop a framework for combining differentiable programming languages with neural networks. Using this framework we create end-to-end trainable systems that learn to write interpretable algorithms with perceptual components. We explore the benefits of inductive …
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Exploring Representation of Horn Clauses using GNNs (Extended Technical Report)
2022 · arXiv (Cornell University)
Learning program semantics from raw source code is challenging due to the complexity of real-world programming language syntax and due to the difficulty of reconstructing long-distance relational information implicitly represented in programs using identifiers. Addressing …
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Structured Neural Summarization
2018 · arXiv (Cornell University)
Summarization of long sequences into a concise statement is a core problem in natural language processing, requiring non-trivial understanding of the input. Based on the promising results of graph neural networks on highly structured data, …