Vertex-Enriched Graph Neural Network (VEGNN)

BotGNN: Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment

Master's thesis : Knowledge Inference and Knowledge Completion Methods using Neuro-Symbolic Inductive Rules

Code for "ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition" (LREC-COLING 2024)

Implementation of a straight-through gradient wrapper to allow for discrete latent representations. Provides binary discretizer which maps hidden representations to {0, 1} and a learnable multi-value discretizer, which maps hidden activations to their closest value in a set of given size.

The official repository for the PSYCHIC model

An attempt to merge ESBN with Transformers, to endow Transformers with the ability to emergently bind symbols

PyEDCR is a package providing error detecting and corrective rules into Python. Given a model, PyEDCR's goal is to recognize when it is incorrect based on a set of conditions and then correct the incorrect prediction.

Pytorch implementation for Perspective Plane Program Induction from a Single Image (P3I).

Tree Stack Memory Units

Usable implementation of Emerging Symbol Binding Network (ESBN), in Pytorch

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

RelNN is a novel first-order deep neural model for relational learning.

Holographic Reduced Representations

[CVPR 2024] Neural Markov Random Field for Stereo Matching

A novel approach to learning concept embeddings and approximate reasoning in ALC knowledge bases with deep neural networks

Lernd is ∂ILP (dILP) framework implementation based on Deepmind's paper Learning Explanatory Rules from Noisy Data.

Neuro-Symbolic AI with Knowledge Graph | "True Reasoning" through data and logic 🌿🌱🐋🌍

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

Python library that enables using prolog syntax and logic programming in python