AutoML-Freiburg-Hannover

Official Implementation of "Transformers Can Do Bayesian Inference"

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A benchmark library for Dynamic Algorithm Configuration.

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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...

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

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A build-it-yourself AutoML Framework

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Presentations on Auto-sklearn

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The first collection of surrogate benchmarks for Joint Architecture and Hyperparameter Search.

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Our maintained PFN repository. Come here to train SOTA PFNs.

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

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