What is recorded here?
Learned reverse-process variances and used modified objectives/noise schedules and importance sampling to improve diffusion likelihood and reduce required sampling steps.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Original DDPM, variational bounds and DDIM retain credit. Learned variance/objective changes are distinct from classifier guidance and later solver algorithms. Quality, likelihood and speed tradeoffs are benchmark dependent.
Read the original work
- Improved Denoising Diffusion Probabilistic Models
- Nichol and Dhariwal: learned-variance and improved-objective diffusion training — author/institutional project
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Alex Nichol; Prafulla Dhariwal
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.
Research locations and affiliations
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English catalogue narrative
Nichol and Dhariwal: learned-variance and improved-objective diffusion training
Learned reverse-process variances and used modified objectives/noise schedules and importance sampling to improve diffusion likelihood and reduce required sampling steps.
Scientific scope
Original DDPM, variational bounds and DDIM retain credit. Learned variance/objective changes are distinct from classifier guidance and later solver algorithms. Quality, likelihood and speed tradeoffs are benchmark dependent.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Alex Nichol; Prafulla Dhariwal
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.