Program induction

16 papers with code • 0 benchmarks • 1 datasets

Generating program code for domain-specific tasks


Greatest papers with code

Learning a Natural Language Interface with Neural Programmer

tensorflow/models 28 Nov 2016

The main experimental result in this paper is that a single Neural Programmer model achieves 34. 2% accuracy using only 10, 000 examples with weak supervision.

Language understanding Program induction +1

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

ellisk42/ec 15 Jun 2020

It builds expertise by creating programming languages for expressing domain concepts, together with neural networks to guide the search for programs within these languages.

Drawing Pictures Program induction +1

Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

deepmind/AQuA 11 May 2017

Solving algebraic word problems requires executing a series of arithmetic operations---a program---to obtain a final answer.

Program induction

Forgetting to learn logic programs

metagol/metagol 15 Nov 2019

To improve learning performance, we explore the idea of forgetting, where a learner can additionally remove programs from its BK.

Inductive logic programming Multi-Task Learning +1

Playgol: learning programs through play

metagol/metagol 18 Apr 2019

In this approach, a program induction system (the learner) is given a set of tasks and initial background knowledge.

Inductive logic programming Program induction

RobustFill: Neural Program Learning under Noisy I/O

amitz25/PCCoder ICML 2017

Recently, two competing approaches for automatic program learning have received significant attention: (1) neural program synthesis, where a neural network is conditioned on input/output (I/O) examples and learns to generate a program, and (2) neural program induction, where a neural network generates new outputs directly using a latent program representation.

Program induction Program Synthesis

Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning

DevinJake/MRL-CQA EMNLP 2020

Our method achieves state-of-the-art performance on the CQA dataset (Saha et al., 2018) while using only five trial trajectories for the top-5 retrieved questions in each support set, and metatraining on tasks constructed from only 1% of the training set.

Knowledge Base Question Answering Meta Reinforcement Learning +1

Strong Generalization and Efficiency in Neural Programs

hardbyte/sorting-gym 7 Jul 2020

We study the problem of learning efficient algorithms that strongly generalize in the framework of neural program induction.

Program induction

DeepProbLog: Neural Probabilistic Logic Programming

MarcRoigVilamala/DeepProbCEP NeurIPS 2018

We introduce DeepProbLog, a probabilistic logic programming language that incorporates deep learning by means of neural predicates.

Program induction

Automatic Discovery of Interpretable Planning Strategies

RationalityEnhancement/InterpretableStrategyDiscovery 24 May 2020

Our algorithm combines recent advances in imitation learning and program induction with a new clustering method for identifying a large subset of demonstrations that can be accurately described by a simple, high-performing decision rule.

Decision Making Imitation Learning +1