AI RESEARCH

TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering

arXiv CS.LG

ArXi:2601.21656v3 Announce Type: replace Clustering tabular data is a fundamental yet challenging problem due to heterogeneous feature types, diverse data-generating mechanisms, and the absence of transferable inductive biases across datasets. Prior-fitted networks (PFNs) have recently nstrated strong generalization in supervised tabular learning by amortizing Bayesian inference under a broad synthetic prior.