Program induction
24 papers with code • 0 benchmarks • 1 datasets
Generating program code for domain-specific tasks
Benchmarks
These leaderboards are used to track progress in Program induction
AQUA-RAT
Most implemented papers
DeepProbLog: Neural Probabilistic Logic Programming
ml-kuleuven/deepproblog
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NeurIPS 2018
We introduce DeepProbLog, a probabilistic logic programming language that incorporates deep learning by means of neural predicates.
RobustFill: Neural Program Learning under Noisy I/O
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.
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
It builds expertise by creating programming languages for expressing domain concepts, together with neural networks to guide the search for programs within these languages.
Learning a Natural Language Interface with Neural Programmer
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.
Forgetting to learn logic programs
To improve learning performance, we explore the idea of forgetting, where a learner can additionally remove programs from its BK.
Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems
Solving algebraic word problems requires executing a series of arithmetic operations---a program---to obtain a final answer.
P-Tree Programming
From this prototype tree we form program instances which we evaluate on a given problem.
Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
In this work, we propose a novel robot learning framework called Neural Task Programming (NTP), which bridges the idea of few-shot learning from demonstration and neural program induction.
Recent Advances in Neural Program Synthesis
In recent years, deep learning has made tremendous progress in a number of fields that were previously out of reach for artificial intelligence.
Playgol: learning programs through play
In this approach, a program induction system (the learner) is given a set of tasks and initial background knowledge.
