Tsetlin Machine for Logical Learning and Reasoning With Graphs
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Apr 13, 2026 - Python
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Tsetlin Machine for Logical Learning and Reasoning With Graphs
graph deep nested-structures convolution message-passing multigraph tsetlin-machine coalesced vector-symbolic-architecture hypervector
Boolean Hypervectors with various operators for experiments in hyperdimensional computing (HDC).
machine-learning computational permutation reasoning winnow majority hyperdimensional-computing vector-symbolic-architecture hypervector binary-spatter-code
A demo showing the benefits of using HDC in a telecom incident scenario
machine-learning prototype hdc vector-search hyperdimensional-computing prototype-learning hypervector
Turn graph data into hypervectors to query them via composable HDC queries
MNIST digit classification with hypervectors
Spektre's state-first protocol canon (1=1) — a prose specification of the coherence invariant, shipped beside the creation-os reference kernel that enforces it in code.
Experiments on bundling in HDC: adding more and more facts to a bundle, handling missing values and more
Hyperdimensional Memory with RG‑Based Cluster Splitting on Real Text
DeepSeek‑φ Hypervector Agent – Full Implementation with Network Communication and all proposed extensions: Thue‑Morse φ‑modulated keys, media adaptation stubs, persistent state, and inter‑agent messaging over TCP.
Multimodal knowledge graphs + HDC with lance-csr and LanceDB
Experiments to understand what we can recover from a bundled MAP hypervector
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