5 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.LG2026★ 3 cited
TabPFN-3: Technical Report
Léo Grinsztajn, Klemens Flöge, Oscar Key +38
Tabular data underpins most high-value prediction problems in science and industry, and TabPFN has driven the foundation model revolution for this modality. Designed with feedback…
cs.LG2025★ 5 cited
From Tables to Time: Extending TabPFN-v2 to Time Series Forecasting
Shi Bin Hoo, Samuel Müller, David Salinas +1
Recent progress in foundation models has enabled strong zero-shot performance for time series forecasting. In this work, we show that such capabilities can also emerge from tabular…