Where does meaning in a hypervector come from?
How projected and learned representations overcome the limitations of random codebooks (which lack semantic structure), bringing useful notions of similarity into hypervector space.
How projected and learned representations overcome the limitations of random codebooks (which lack semantic structure), bringing useful notions of similarity into hypervector space.
An introduction to the role of permutation in hyperdimensional computing and how it preserves structural information in ways that multiplicative binding cannot.
How the problem of representing structured knowledge in distributed systems gave rise to the family now known as HDC and VSA.
How Hyperdimensional Computing distributes information across an entire hypervector, helping representations degrade gradually under noise.
A closer look at the high-dimensional, distributed mathematical objects that give hyperdimensional computing its unusual geometry.
A gentle introduction to how hyperdimensional computing represents, combines, and retrieves information using high-dimensional hypervectors.
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