Dan Hendrycks
Impact in
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 1%
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Natural Language Processing Techniques
Papers in
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- Adversarial Robustness in Machine Learning 13
- Anomaly Detection Techniques and Applications 9
- Explainable Artificial Intelligence (XAI) 2
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- Advanced Neural Network Applications 4
- Co-authors
- Dawn Song (7 shared papers)Jacob Steinhardt (5 shared papers)Steven Basart (6 shared papers)Mantas Mazeika (6 shared papers)Kevin Zhao (1 shared paper)Saurav Kadavath (2 shared papers)Justin Gilmer (3 shared papers)Norman Mu (2 shared papers)
- Journals
- Patterns (1 paper)Proceedings of the VLDB Endowment (1 paper)Lecture notes in computer science (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)International Conference on Learning Representations (2 papers)
- Partner nations
- United StatesSingaporeJapan
In The Last Decade
Dan Hendrycks
20 papers receiving 1.8k citations
Dan Hendrycks's Hit Papers
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 890
- Artificial Intelligence 1.4k
- Health Informatics 45
- Signal Processing 88
- Safety Research 50
Countries citing papers authored by Dan Hendrycks
This map shows the geographic impact of Dan Hendrycks'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 Dan Hendrycks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Hendrycks more than expected).
Fields of papers citing papers by Dan Hendrycks
This network shows the impact of papers produced by Dan Hendrycks. 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 Dan Hendrycks. The network helps show where Dan Hendrycks may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Hendrycks, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Hit paper breakdown → | 2021 | 622 |
| 2 | Natural Adversarial Examples Hit paper breakdown → | 2021 | 472 |
| 3 | Measuring Massive Multitask Language Understanding Hit paper breakdown → | 2021 | 203 |
| 4 | 2018 | 127 | |
| 5 | Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty | 2019 | 87 |
| 6 | AI deception: A survey of examples, risks, and potential solutions Hit paper breakdown → | 2024 | 74 |
| 7 | AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty | 2020 | 67 |
| 8 | 2022 | 59 | |
| 9 | Early Methods for Detecting Adversarial Images | 2017 | 47 |
| 10 | 2024 | 33 | |
| 11 | A Benchmark for Anomaly Segmentation. | 2019 | 24 |
| 12 | 2019 | 14 | |
| 13 | Visible Progress on Adversarial Images and a New Saliency Map. | 2016 | 11 |
| 14 | 2024 | 9 | |
| 15 | 2019 | 7 | |
| 16 | 2023 | 6 | |
| 17 | 2022 | 5 | |
| 18 | A Quantitative Measure of Generative Adversarial Network Distributions | 2017 | 2 |
| 19 | Generalizing and Improving Weight Initialization. | 2016 | 1 |
| 20 | CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review | 2021 | 1 |
About Dan Hendrycks
Dan Hendrycks is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Political Science and International Relations and Computer Networks and Communications, having authored 23 papers that have together received 1.9k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (13 papers), Anomaly Detection Techniques and Applications (9 papers), Advanced Malware Detection Techniques (4 papers), Advanced Neural Network Applications (4 papers), Artificial Intelligence in Law (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Ethics and Social Impacts of AI (1 paper) and Network Security and Intrusion Detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (890 citations), Artificial Intelligence (1.4k citations), Health Informatics (45 citations), Signal Processing (88 citations) and Safety Research (50 citations). Dan Hendrycks has collaborated with scholars based in United States, Singapore and Japan. Frequent co-authors include Dawn Song, Jacob Steinhardt, Steven Basart, Mantas Mazeika, Kevin Zhao, Saurav Kadavath, Justin Gilmer, Norman Mu, Fengqiu Wang and Tyler Zhu. Their work appears in journals such as Patterns, Proceedings of the VLDB Endowment, Lecture notes in computer science, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and International Conference on Learning Representations.
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.