Methods › General › Deep Tabular Learning › GrowNet
GrowNet
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
GrowNet is a novel approach to combine the power of gradient boosting to incrementally build complex deep neural networks out of shallow components. It introduces a versatile framework that can readily be adapted for a diverse range of machine learning tasks in a wide variety of domains.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Gradient Boosting Neural Networks: GrowNet 19 Feb 2020 · 1 repository · arXiv:2002.07971Syntology ran 3 of 6 samples · 3 unverified · 6 pointer-only (licence)
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Learning-To-Rank | 1 |
| regression | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections