The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected

Framework and Language for Neurosymbolic Programming.

Machine Learning with Symbolic Tensors

An explainable inference software supporting annotated, real valued, graph based and temporal logic

A curated paper list on neural symbolic and probabilistic logic.

Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform human-designed algorithms

mOWL: Machine Learning library with Ontologies

PyTorch code for the RetoMaton paper: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022)

Experimental Python implementation of the Clarion cognitive architecture

Domain-Aware Neurosymbolic Agent (Dana), an agent-native programming language

A collection of neuro-symbolic systems, papers and videos

TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning

Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming

Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

[TPAMI] "Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search", Wenqing Zheng*, S P Sharan*, Zhiwen Fan, Kevin Wang, Yihan Xi, Atlas Wang

A Scalable Approximate Method for Probabilistic Neurosymbolic Inference

🧮 Algebraic Positional Encodings.

Sparse Circuits on the GPU (ICLR2025)

Code for the ICLR 2024 paper "How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data"

PyC (Pytorch Concepts) is a PyTorch-based library for training concept-based interpretable deep learning models.