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Program induction

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/CatherineWong/dreamcoder

공식 코드

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

https://github.com/DevinJake/MRL-CQA

공식 코드

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

https://github.com/RationalityEnhancement/InterpretableStrategyDiscovery

공식 코드

Automatic Discovery of Interpretable Planning Strategies

https://github.com/andrewcropper/aaai20-forgetgol

공식 코드

Forgetting to learn logic programs

https://github.com/clement-bonnet/lpn

공식 코드

Searching Latent Program Spaces

https://github.com/coesch/ptree

공식 코드

P-Tree Programming

https://github.com/deep-symbolic-mathematics/llm-sr

공식 코드

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

https://github.com/deepmind/AQuA

공식 코드

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

https://github.com/dki-lab/arcaneqa

공식 코드

ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering

https://github.com/esennesh/categorical_bpl

공식 코드

Learning a Deep Generative Model like a Program: the Free Category Prior

https://github.com/metagol/metagol

공식 코드

Playgol: learning programs through play

https://github.com/ml-kuleuven/deepproblog

공식 코드

DeepProbLog: Neural Probabilistic Logic Programming

https://github.com/ml-research/neumann

공식 코드

Learning Differentiable Logic Programs for Abstract Visual Reasoning

https://github.com/s72sue/map-induction

공식 코드

Map Induction: Compositional spatial submap learning for efficient exploration in novel environments

https://github.com/sebdumancic/knorf_aaai21

공식 코드

Knowledge Refactoring for Inductive Program Synthesis

https://github.com/sreejank/language_and_programs

공식 코드

Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines

https://github.com/tensorflow/models

공식 코드

Learning a Natural Language Interface with Neural Programmer

https://github.com/thu-keg/kb-plugin

공식 코드

KB-Plugin: A Plug-and-play Framework for Large Language Models to Induce Programs over Low-resourced Knowledge Bases

https://github.com/thu-keg/programtransfer

공식 코드

Program Transfer for Answering Complex Questions over Knowledge Bases

https://bitbucket.org/problog/deepproblog

DeepProbLog: Neural Probabilistic Logic Programming

https://github.com/MarcRoigVilamala/DeepProbCEP

DeepProbLog: Neural Probabilistic Logic Programming

https://github.com/StanfordVL/arxivbot

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

https://github.com/amitz25/PCCoder

RobustFill: Neural Program Learning under Noisy I/O

https://github.com/dais-ita/deepprobcep

DeepProbLog: Neural Probabilistic Logic Programming

https://github.com/ellisk42/ec

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

https://github.com/gpoesia/peano

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

https://github.com/hardbyte/sorting-gym

Strong Generalization and Efficiency in Neural Programs

https://github.com/insperatum/pinn

RobustFill: Neural Program Learning under Noisy I/O

https://github.com/jhcircle/less-is-more

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

https://github.com/pramodkaushik/np_analysis

Learning a Natural Language Interface with Neural Programmer

https://github.com/qu-arx/arx-inf

Recent Advances in Neural Program Synthesis

https://github.com/yeoedward/Robust-Fill

RobustFill: Neural Program Learning under Noisy I/O

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.