Papers Program induction
“Program induction” 태그가 달린 논문 67편 · 필터 해제
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version)
Extending the success of deep neural networks to natural language understanding and symbolic reasoning requires complex operations and external memory. Recent neural program induction approaches have attempted to address…
Feature EngineeringNatural Language UnderstandingProgram inductionSemantic ParsingSummary - TerpreT: A Probabilistic Programming Language for Program Induction
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-spe…
Probabilistic ProgrammingProgram inductionProgram SynthesisProbabilistic Neural Programs
We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural n…
Program inductionQuestion AnsweringLearning a Natural Language Interface with Neural Programmer
Learning a natural language interface for database tables is a challenging task that involves deep language understanding and multi-step reasoning. The task is often approached by mapping natural language queries to logi…
Natural Language QueriesProgram inductionQuestion AnsweringPrograms as Black-Box Explanations
Recent work in model-agnostic explanations of black-box machine learning has demonstrated that interpretability of complex models does not have to come at the cost of accuracy or model flexibility. However, it is not cle…
Program inductionNeuro-Symbolic Program Synthesis
Recent years have seen the proposal of a number of neural architectures for the problem of Program Induction. Given a set of input-output examples, these architectures are able to learn mappings that generalize to new te…
Program inductionProgram SynthesisTerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; given input-output examples, we try to synthesize source code that maps inputs to corresponding outputs. Our aims are to develop new machine learning…
BIG-bench Machine LearningProbabilistic ProgrammingProgram inductionProgram Synthesis