automl

Automated Machine Learning with scikit-learn

Automatic architecture search and hyperparameter optimization for PyTorch

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

a distributed Hyperband implementation on Steroids

NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.

RoBO: a Robust Bayesian Optimization framework

Auto-WEKA

Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper

A curated list of awesome resources combining Transformers with Neural Architecture Search

Domain specific language for configuration spaces in Python. Useful for hyperparameter optimization and algorithm configuration.

Lightweight and educational reimplementation of TabPFN https://arxiv.org/pdf/2511.03634

Benchmarking RL generalization in an interpretable way.

Collection of hyperparameter optimization benchmark problems

HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization packages: SMAC, spearmint and hyperopt. This package is...

This is the official implementation of TrivialAugment and a mini-library for the application of multiple image augmentation strategies including RandAugment and TrivialAugment.

Understanding and Robustifying DARTS

Bayesian neural network package

A Playground for Tabular Foundation Models

An interactive framework to visualize and analyze your AutoML process in real-time.

Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.

Parameter Importance Analysis Tool

A build-it-yourself AutoML Framework

End-to-end RNA Design using deep reinforcement learning

BOAH: Bayesian Optimization & Analysis of Hyperparameters

The Mighty cRL library you've been looking for!

An extension to Sacred for automated hyperparameter optimization.

TempoPFN: Zero-shot Time Series Forecasting (accepted at NeurIPS 2026)

Mamba4Cast, a zero-shot time series forecasting model, achieves competitive performance and faster inference than transformer-based models by leveraging Mamba architecture and synthetic training...

The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization