Paper collection on building and evaluating language model agents via executable language grounding
Reasoning Computers. Lambda Calculus, Fully Differentiable. Also Neural Stacks, Queues, Arrays, Lists, Trees, and Latches.
Offical Repo for "Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale"
A curated paper list on neural symbolic and probabilistic logic.
AIKA (Artificial Intelligence for Knowledge Acquisition) is an innovative approach to neural network design, diverging from traditional architectures that rely heavily on rigid matrix and vector operations. The AIKA Project introduces a flexible, sparse, and non-layered network representation, derived from a type hierarchy.
mOWL: Machine Learning library with Ontologies
Neural-Grammar-Symbolic Learning with Back-Search
Explainable complex question answering over RDF files via Llama Index.
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System.
Symbolic DNN-Tuner is a system to drive the training of a Deep Neural Network, analysing the performance of each training experiment and automatizing the choice of HPs to obtain a network with better performance.
NeuroLog: A Neural-Symbolic System
Jupyter notebooks with examples of Logical Neural Networks (LNN) by IBM
Implementation of a new scenario for the Neural-Symbolic system NEUROLOG
NEural-symbolic Entity Reasoning and Matching in Python
NEural-symbolic Entity Reasoning and Matching in R
Add a description, image, and links to the neural-symbolic topic page so that developers can more easily learn about it.
To associate your repository with the neural-symbolic topic, visit your repo's landing page and select "manage topics."