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@hyperdimensionalcomputingai

Hyperdimensional Computing Labs

A practical approach toward brain-inspired cognitive computing that combines graphs with vector-symbolic architectures.

HDC Labs

Applied research, development, and advisory in hyperdimensional computing.

We work at the intersection of hyperdimensional computing (HDC), graph intelligence, and agentic systems. We design hypervector representations for real tasks, benchmark them against established approaches, and publish what we learn.

Our current interests include:

  • connected and heterogeneous data
  • associative search and agent memory
  • online learning from small numbers of examples
  • practical combinations of HDC, graphs, and deep learning

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  1. intro-to-hdc intro-to-hdc Public

    Multimodal knowledge graphs + HDC with lance-csr and LanceDB

    Python

  2. lance-csr lance-csr Public

    A maintained fork of lance-graph. A Fast Cypher query engine over Lance datasets, built on DataFusion with a CSR adjacency index.

    Rust 16 1

  3. graph-benchmark-ldbc graph-benchmark-ldbc Public

    Graph benchmarks for Ladybug, Kuzu, lance-csr and DuckPGQ on LDBC SNB dataset

    Python 8 6

  4. graph-to-hypervectors graph-to-hypervectors Public

    Turn graph data into hypervectors to query them via composable HDC queries

    Python 1

  5. bundling-capacity bundling-capacity Public

    Experiments on bundling in HDC: adding more and more facts to a bundle, handling missing values and more

    Python 1

  6. telecom-incident-triage telecom-incident-triage Public

    A demo showing the benefits of using HDC in a telecom incident scenario

    Python 1

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