71 citations · 73 across the 3 of their papers we have counts for
3 papers
Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes
Mayuka Jayawardhana, Renbo, Samuel Dooley +6
Large language models (LLMs) perform remarkably well on tabular datasets in zero- and few-shot settings, since they can extract meaning from natural language column headers that de…
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova +5
While tabular classification has traditionally relied on from-scratch training, a recent breakthrough called prior-data fitted networks (PFNs) challenges this approach. Similar to…
When Do Neural Nets Outperform Boosted Trees on Tabular Data?
Duncan McElfresh, Sujay Khandagale, Jonathan Valverde +6
Tabular data is one of the most commonly used types of data in machine learning. Despite recent advances in neural nets (NNs) for tabular data, there is still an active discussion…