Frank Hutter

papers

1,436

total citations

papers (22)

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

NEURIPS 2023arXiv

111

citations

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies

NEURIPS 2022arXiv

citations

Joint Entropy Search For Maximally-Informed Bayesian Optimization

NEURIPS 2022arXiv

citations

Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks

NEURIPS 2023arXiv

citations

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

NEURIPS 2023arXiv

citations

NAS-Bench-x11 and the Power of Learning Curves

NEURIPS 2021arXiv

citations

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

NEURIPS 2023arXiv

citations

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

ICML 2024arXiv

citations

DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products

NEURIPS 2025arXiv

citations

Self-Correcting Bayesian Optimization through Bayesian Active Learning

NEURIPS 2023arXiv

citations

Position: A Call to Action for a Human-Centered AutoML Paradigm

ICML 2024arXiv

citations

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design

NEURIPS 2022arXiv

citations

Do-PFN: In-Context Learning for Causal Effect Estimation

NEURIPS 2025arXiv

citations

Surprisingly Strong Performance Prediction with Neural Graph Features

ICML 2024arXiv

citations

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars

NEURIPS 2023arXiv

citations

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

ICML 2025arXiv

citations

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

NEURIPS 2021arXiv

citations

JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search

NEURIPS 2022

citations

Frank Hutter

papers (22)

TrivialAugment: Tuning-Free Yet State-of-the-Art Data Augmentation

Well-tuned Simple Nets Excel on Tabular Datasets

Meta-Learning of Neural Architectures for Few-Shot Learning

How Powerful are Performance Predictors in Neural Architecture Search?

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies

Joint Entropy Search For Maximally-Informed Bayesian Optimization

Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

NAS-Bench-x11 and the Power of Learning Curves

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products

Self-Correcting Bayesian Optimization through Bayesian Active Learning

Position: A Call to Action for a Human-Centered AutoML Paradigm

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design

Do-PFN: In-Context Learning for Causal Effect Estimation

Surprisingly Strong Performance Prediction with Neural Graph Features

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search

papers (22)

TrivialAugment: Tuning-Free Yet State-of-the-Art Data Augmentation

Well-tuned Simple Nets Excel on Tabular Datasets

Meta-Learning of Neural Architectures for Few-Shot Learning

How Powerful are Performance Predictors in Neural Architecture Search?

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies

Joint Entropy Search For Maximally-Informed Bayesian Optimization

Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

NAS-Bench-x11 and the Power of Learning Curves

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products

Self-Correcting Bayesian Optimization through Bayesian Active Learning

Position: A Call to Action for a Human-Centered AutoML Paradigm

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design

Do-PFN: In-Context Learning for Causal Effect Estimation

Surprisingly Strong Performance Prediction with Neural Graph Features

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search