PyTorch implementation for the Neuro-Symbolic Concept Learner (NS-CL).
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Updated
Oct 24, 2020 - Python
PyTorch implementation for the Neuro-Symbolic Concept Learner (NS-CL).
Implementation for the Neural Logic Machines (NLM).
Python library that enables using prolog syntax and logic programming in python
[CVPR 2024] Neural Markov Random Field for Stereo Matching
An efficient Python toolkit for Abductive Learning (ABL), a novel paradigm that integrates machine learning and logical reasoning in a unified framework.
Lernd is ∂ILP (dILP) framework implementation based on Deepmind's paper Learning Explanatory Rules from Noisy Data.
Usable implementation of Emerging Symbol Binding Network (ESBN), in Pytorch
Holographic Reduced Representations
Tree Stack Memory Units
An attempt to merge ESBN with Transformers, to endow Transformers with the ability to emergently bind symbols
Pytorch implementation for Perspective Plane Program Induction from a Single Image (P3I).
BotGNN: Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment
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.
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