tabpfn

⚡ TabPFN: Foundation Model for Tabular Data ⚡

Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)

Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗

⚡ Easy API access to the tabular foundation model TabPFN ⚡

Semi-automatic feature engineering process using Language Models and your dataset descriptions. Based on the paper "LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering" by Hollmann, Müller, and Hutter (2023).

Code for finetuning TabPFN on one downstream tabular dataset.

A curated collection of papers, repositories, and resources on Prior-data Fitted Networks (PFNs).

🚀 Awesome TabPFN use-cases from around the world

TabPFGen: Synthetic Tabular Data Generation with TabPFN

On Finetuning Tabular Foundation Models Paper Code

An ensemble-based, size-agnostic wrapper around the TabPFN classifier for chemical datasets.

Turning Tabular Foundation Models into Graph Foundation Models

GOTabPFN: Graph-guided feature ordering and compact tokenization for TabPFN-style tabular foundation models on high-dimensional data.

[ICML 2024] TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting

TFG realizado en la Universidad de Burgos del desarrollo de una aplicación para el uso de un Radar de 60 GHz de la marca Acconeer.

Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference

DuckDB extension for tabular foundation models — zero-shot classification & regression in SQL. Built-in Mitra, TabPFN v2, TabICL v2, and Google TabFM (selectable by name); register your own in SQL. ONNX Runtime CPU/CUDA/ROCm.

TabPFN implementation with PyTorch

A comprehensive pipeline for multi-model classification of PET/CT radiomics data, including individual classifiers and decision-level fusion via soft voting. ROC curves are used to evaluate performance on both individual models and the ensemble.

My Small PFN — a competitive proof-of concept for Prior-Data Fitted Networks