Deep learning· 2006
A Fast Learning Algorithm for Deep Belief Nets
On the reading lists
- #69 in the Top 500 (2026 edition)
- #11 in Deep learning (2026 edition)
Why it matters
Demonstrated effective greedy layerwise training, helping revive research into deep neural networks.
Condensed from the expert lists' notes.
The record
- First released
- 2006 (from OpenAlex)
- Citations
- 16,335 citations, as counted by OpenAlex (CC0)
- Named by
- both expert lists
- Also relevant to
- Generative models, Computer vision & multimodal
- Score
- 0.704 · computed rank 69 · consensus 0.79, must-read 1, citations percentile 0.907 (2000s · all domains), awards 0, existing lists 0.5. Method
Editor's notes
- Readability check: fail: Historically important, but the greedy layer-wise method is no longer used and the paper is hard going. (AI draft (Claude), not yet reviewed, 2026-10-29)
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.