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NeurIPS 2026U MannheimPrior LabsAWS AISiemens Corporate ResearchU RostockTabular data

TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks

TabPrep is a lightweight feature engineering pipeline that targets structural data patterns to consistently boost tabular model performance across benchmarks.

Andrej Tschalzev, Nick Erickson, Yuyang (Bernie) Wang, Huzefa Rangwala and 3 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
83%Must read
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NeurIPS 2026TsinghuaTsinghua University, TsinghuaStableAISoutheastSiemens Corporate ResearchDiffusion models

Breaking the Quality–Privacy Tradeoff in Tabular Data Generation via In-Context Learning

DiffICL frames tabular synthesis as in-context learning using pretrained structural priors to avoid memorization, improving both quality and privacy in small-data settings.

Xinyan Han, yan Lu, Xiaoyu Lin, Yuanyuan Jiang and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5