Neuro-Symbolic AI with Knowledge Graph 🚀 Current Knowledge Graphs are outdated or extremely primitive, Nucleoid is revolutionizing knowledge graph with logic graph to get next step in the journey to AGI 🌿🌱🐋🌍

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

PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT

AIKA is a new type of artificial neural network designed to more closely mimic the behavior of a biological brain and to bridge the gap to classical AI. A key design decision in the Aika network is to conceptually separate the activations from their neurons, meaning that there are two separate graphs. One graph consisting of neurons and synapses…

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

mOWL: Machine Learning library with Ontologies

Neuro-Symbolic Visual Question Answering on Sort-of-CLEVR using PyTorch

Hrrformer: A Neuro-symbolic Self-attention Model (ICML23)

An efficient Python toolkit for Abductive Learning (ABL), a novel paradigm that integrates machine learning and logical reasoning in a unified framework.

Neuro-Symbolic Reinforcement Learning: Logical Optimal Action (LOA), a novel RL with Logical Neural Network (LNN) on text-based games

[ACL 2024] The project of Symbol-LLM

LLM Dynamic Planner - Combining LLM with PDDL Planners to solve an embodied task

ZeroC is a neuro-symbolic method that trained with elementary visual concepts and relations, can zero-shot recognize and acquire more complex, hierarchical concepts, even across domains

Self's foundational abstractions

Holographic Reduced Representations

Codebase for Neuro-Symbolic Continual Learning.

Demo for Neuro-Symbolic Agent (LOA)

Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning

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

program synthesis with neuro-symbolic differentiable interpreters