Alternatives and similar repositories for awesome-program

Users that are interested in awesome-program are comparing it to the libraries listed below

• Jungyhuk / latent-execution
  ☆25Updated 3 years ago
• clvrai / leaps
  Code for Learning to Synthesize Programs as Interpretable and Generalizable Policies in NeurIPS 2021
  ☆37Updated 2 years ago
• shrivastavadisha / N-PEPS
  ☆18Updated 3 years ago
• bunelr / GandRL_for_NPS
  Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis
  ☆38Updated 2 years ago
• flxsosa / ProgramSearch
  A public repository for "Write, Execute, Assess: Program Synthesis With a REPL" project by Kevin Ellis, Max Nye, Yewen Pu, Felix Sosa, Jo…
  ☆38Updated 5 years ago
• google-research / crossbeam
  ☆43Updated 2 years ago
• albertqjiang / INT
  Official code for paper: INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
  ☆39Updated 2 years ago
• mtensor / rulesynthesis
  Code for "Learning Compositional Rules via Neural Program Synthesis"
  ☆60Updated 4 years ago
• nathanael-fijalkow / DeepSynth
  General-purpose program synthesiser
  ☆45Updated 8 months ago
• liqing-ustc / NGS
  Neural-Grammar-Symbolic Learning with Back-Search
  ☆54Updated 11 months ago
• thuwzy / Neural-Symbolic-and-Probabilistic-Logic-Papers
  A curated paper list on neural symbolic and probabilistic logic.
  ☆129Updated last year
• mlb2251 / stitch
  A scalable abstraction learning library
  ☆80Updated this week
• xiye17 / SAT-LM
  SatLM: SATisfiability-Aided Language Models using Declarative Prompting (NeurIPS 2023)
  ☆49Updated 11 months ago
• carpedm20 / karel
  Karel dataset for program synthesis and program induction
  ☆79Updated 7 years ago
• trishullab / near
  ☆24Updated 4 years ago
• google-research / plur
  PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. W…
  ☆88Updated 3 years ago
• shihui2010 / symbolic_simplifier
  PyTorch implementation for the Deep Symbolic Simplification Without Human Knowledge
  ☆14Updated 4 years ago
• pdlan / OSCAR
  Code for ICML 2021 paper: How could Neural Networks understand Programs?
  ☆124Updated 7 months ago
• zhaoyu-li / DL4TP
  [COLM 2024] A Survey on Deep Learning for Theorem Proving
  ☆192Updated last month
• satwik77 / Transformer-Formal-Languages
  EMNLP 2020: On the Ability and Limitations of Transformers to Recognize Formal Languages
  ☆24Updated 4 years ago
• eth-sri / dl2
  DL2 is a framework that allows training neural networks with logical constraints over numerical values in the network (e.g. inputs, out…
  ☆86Updated 11 months ago
• rfeinman / GNS-Modeling
  Generative Neuro-Symbolic (GNS) Modeling (Feinman & Lake, 2021)
  ☆27Updated 3 years ago
• trishullab / houdini
  HOUDINI: Lifelong Learning as Program Synthesis
  ☆48Updated 3 months ago
• neurosymbolic-learning / Neurosymbolic_Tutorial
  Python notebooks for a tutorial on neurosymbolic programming
  ☆75Updated last year
• joshuacnf / paradox-learning2reason
  ☆34Updated 6 months ago
• mtensor / neural_sketch
  neural sketch project, currently in generative regex, list transformation (deepcoder), and text editing (robustfill) domains
  ☆24Updated 5 years ago
• nearai / program_synthesis
  Program Synthesis
  ☆145Updated 4 years ago
• kavigupta / neurosym-lib
  Neurosymbolic Library
  ☆25Updated this week
• princeton-nlp / TransformerPrograms
  [NeurIPS 2023] Learning Transformer Programs
  ☆161Updated last year
• parasj / contracode
  Contrastive Code Representation Learning: functionality-based JavaScript embeddings through self-supervised learning
  ☆167Updated 3 years ago