Frank Hutter
- Artificial Intelligence top 0.1%
- Machine Learning and Data Classification 50
- Machine Learning and Algorithms 35
- Metaheuristic Optimization Algorithms Research 12
- Adversarial Robustness in Machine Learning 6
- Cognitive Neuroscience top 0.5%
- Computational Theory and Mathematics top 0.2%
- Advanced Multi-Objective Optimization Algorithms 25
- Software top 1%
- Model-Driven Software Engineering Techniques 5
- Signal Processing top 0.5%
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- Constraint Satisfaction and Optimization 9
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- Advanced Neural Network Applications 9
- Co-authors
- Holger H. HoosKevin Leyton‐BrownJost Tobias SpringenbergKatharina EggenspergerIlya LoshchilovJoaquin VanschorenLars KotthoffRobin Tibor Schirrmeister
- Journals
- Journal of Artificial Intelligence Research (8 papers)Artificial Intelligence (2 papers)Clinical Neurophysiology (1 paper)
- Partner nations
- GermanyCanadaUnited Kingdom
In The Last Decade
Frank Hutter
105 papers receiving 9.7k citations
Hit Papers
Peers
Comparison fields: 5 of 198
- Artificial Intelligence 5.0k
- Cognitive Neuroscience 2.2k
- Computational Theory and Mathematics 1.3k
- Software 302
- Signal Processing 803
Countries citing papers authored by Frank Hutter
This map shows the geographic impact of Frank Hutter's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Frank Hutter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Hutter more than expected).
Fields of papers citing papers by Frank Hutter
This network shows the impact of papers produced by Frank Hutter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Frank Hutter. The network helps show where Frank Hutter may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Frank Hutter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Accurate predictions on small data with a tabular foundation modelbreakdown → | 2025 | 106 |
| 2 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 10 | |
| 5 | On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning | 2021 | 3 |
| 6 | Best Practices for Scientific Research on Neural Architecture Search | 2020 | 2 |
| 7 | Understanding and Robustifying Differentiable Architecture Search | 2020 | 41 |
| 8 | Multi-objective Architecture Search for CNNs. | 2018 | 10 |
| 9 | Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks | 2018 | 3 |
| 10 | 2017 | 20 | |
| 11 | Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. | 2017 | 41 |
| 12 | Deep learning with convolutional neural networks for EEG decoding and visualizationbreakdown → | 2017 | 2114 |
| 13 | 2017 | 20 | |
| 14 | Towards Automatically-Tuned Neural Networks | 2016 | 60 |
| 15 | An automatically configured algorithm selector | 2015 | 1 |
| 16 | Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves | 2015 | 200 |
| 17 | Automatic algorithm configuration based on local search | 2007 | 138 |
| 18 | 2007 | 56 | |
| 19 | Performance prediction and automated tuning of randomized and parametric algorithms | 2006 | 17 |
| 20 | Efficient stochastic local search for MPE solving | 2005 | 25 |
About Frank Hutter
Frank Hutter is a scholar working on Software, Artificial Intelligence and Computational Theory and Mathematics, having authored 109 papers that have together received 10.1k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (50 papers), Machine Learning and Algorithms (35 papers), Advanced Multi-Objective Optimization Algorithms (25 papers), Metaheuristic Optimization Algorithms Research (12 papers), Constraint Satisfaction and Optimization (9 papers), Advanced Neural Network Applications (9 papers), Adversarial Robustness in Machine Learning (6 papers) and Model-Driven Software Engineering Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (5.0k citations), Cognitive Neuroscience (2.2k citations) and Computational Theory and Mathematics (1.3k citations). Frank Hutter has collaborated with scholars based in Germany, Canada and United Kingdom. Frequent co-authors include Holger H. Hoos, Kevin Leyton‐Brown, Jost Tobias Springenberg, Katharina Eggensperger, Ilya Loshchilov, Joaquin Vanschoren, Lars Kotthoff, Robin Tibor Schirrmeister, Tonio Ball and Wolfram Burgard. Their work appears in journals such as Journal of Artificial Intelligence Research, Artificial Intelligence, Clinical Neurophysiology, NeuroImage and Nature.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.