104 citations · 145 across the 11 of their papers we have counts for
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cs.LG2023★ 3 cited
PFNs4BO: In-Context Learning for Bayesian Optimization
Samuel Müller, Matthias Feurer, Noah Hollmann +1
In this paper, we use Prior-data Fitted Networks (PFNs) as a flexible surrogate for Bayesian Optimization (BO). PFNs are neural processes that are trained to approximate the poster…
cs.AI2023★ 7 cited
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Noah Hollmann, Samuel Müller, Frank Hutter
As the field of automated machine learning (AutoML) advances, it becomes increasingly important to incorporate domain knowledge into these systems. We present an approach for doing…