What changed
Developed tractable invertible generative models through additive coupling, affine coupling with learned scale, and Glow's invertible1x1 channel mixing and ActNorm within multiscale architectures.
Scientific scope
Developed tractable invertible generative models through additive coupling, affine coupling with learned scale, and Glow's invertible1x1 channel mixing and ActNorm within multiscale architectures. A chronological family, not one joint paper. Exact density is under the continuous model, not proof of matching real data; image dequantization/preprocessing matters. NICE's unit-determinant additive blocks, Real NVP's affine blocks and Glow's channel mixing remain separately attributed. Invertible1x1 weights must remain nonsingular; ActNorm is data-initialized, not ordinary batch normalization.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. A chronological family, not one joint paper. Exact density is under the continuous model, not proof of matching real data; image dequantization/preprocessing matters. NICE's unit-determinant additive blocks, Real NVP's affine blocks and Glow's channel mixing remain separately attributed. Invertible1x1 weights must remain nonsingular; ActNorm is data-initialized, not ordinary batch normalization.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
- NICE: Non-linear Independent Components Estimation
- Density estimation using Real NVP
- Glow: Generative Flow with Invertible 1x1 Convolutions
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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