Program induction
22 papers with code • 0 benchmarks • 1 datasets
Generating program code for domain-specific tasks
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AQUA-RAT
Latest papers with no code
Flexible Compositional Learning of Structured Visual Concepts
Humans are highly efficient learners, with the ability to grasp the meaning of a new concept from just a few examples.
Fast and flexible: Human program induction in abstract reasoning tasks
The Abstraction and Reasoning Corpus (ARC) is a challenging program induction dataset that was recently proposed by Chollet (2019).
Abstraction and Analogy-Making in Artificial Intelligence
Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains.
Multi-Plane Program Induction with 3D Box Priors
We consider two important aspects in understanding and editing images: modeling regular, program-like texture or patterns in 2D planes, and 3D posing of these planes in the scene.
Measuring few-shot extrapolation with program induction
Program induction lies at the opposite end of the spectrum: programs are capable of extrapolating from very few examples, but we still do not know how to efficiently search for complex programs.
Learning abstract structure for drawing by efficient motor program induction
Humans flexibly solve new problems that differ qualitatively from those they were trained on.
Learning to learn generative programs with Memoised Wake-Sleep
We study a class of neuro-symbolic generative models in which neural networks are used both for inference and as priors over symbolic, data-generating programs.
Perspective Plane Program Induction from a Single Image
We study the inverse graphics problem of inferring a holistic representation for natural images.
Attention on Abstract Visual Reasoning
Our proposed hybrid model, represents an alternative on learning abstract relations using self-attention and demonstrates that the Transformer network is also well suited for abstract visual reasoning.
Neural Probabilistic Logic Programming in DeepProbLog
We introduce DeepProbLog, a neural probabilistic logic programming language that incorporates deep learning by means of neural predicates.
