Jupyter notebooks with examples of Logical Neural Networks (LNN) by IBM
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Updated
Mar 23, 2022
Jupyter notebooks with examples of Logical Neural Networks (LNN) by IBM
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System.
NeuroLog: A Neural-Symbolic System
Implementation of a new scenario for the Neural-Symbolic system NEUROLOG
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.
mOWL: Machine Learning library with Ontologies
Explainable complex question answering over RDF files via Llama Index.
Neural-Grammar-Symbolic Learning with Back-Search
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"
Paper collection on building and evaluating language model agents via executable language grounding
A curated paper list on neural symbolic and probabilistic logic.
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…
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