PeterOvermann/TriadicMemory
Cognitive Computing with Associative Memory
This project provides advanced associative memory algorithms for cognitive computing. It takes in sparse binary data representations, often called hypervectors, and processes them to store and recall relationships or predict future sequences. This is ideal for researchers and practitioners working with neural networks, semantic information, or temporal pattern recognition.
No commits in the last 6 months.
Use this if you need to store and retrieve complex relationships between sparse binary data, or if you're building systems that learn and predict sequences from such data.
Not ideal if your data is not easily represented as sparse binary hypervectors, or if you require traditional statistical machine learning models.
Stars
37
Forks
14
Language
Mathematica
License
MIT
Category
Last pushed
Feb 11, 2024
Commits (30d)
0
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