Codebook
A core tool in qualitative research and content analysis that contains category definitions, decision rules, decision trees, and representative examples. It is used to guide human or AI annotators in classifying and coding text consistently.
Timeline (last 90 days)
The core of VQ-VAE is a learnable codebook containing a number of discrete vectors; after the encoder outputs continuous representations, each position is replaced with the nearest vector in the codebook (nearest-neighbor quantization).
Vector quantization (VQ) maps a group of weights as a whole to the nearest codeword in a pre-learned codebook, storing only the codeword index.
All Facts (2)
The core of VQ-VAE is a learnable codebook containing a number of discrete vectors; after the encoder outputs continuous representations, each position is replaced with the nearest vector in the codebook (nearest-neighbor quantization).
50%UnverifiedVector quantization (VQ) maps a group of weights as a whole to the nearest codeword in a pre-learned codebook, storing only the codeword index.
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