TabPFN

TabPFN is a machine learning model for tabular datasets proposed in 2022. It uses a transformer architecture. It is intended for supervised classification and regression analysis on small- to medium-sized datasets, e.g., up to 10,000 samples. TabPFN-2.5 is the latest version of the foundation model.

Two-hop subgraph: this entity, every entity it directly relates to, and every entity those neighbors relate to. Drag a node, scroll to zoom, click to inspect — or click any neighbor and re-center the atlas there.