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

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

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.

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