Dan Hendrycks
Impact in
- 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
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
Papers in ⓘ
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- Adversarial Robustness in Machine Learning 12
- Anomaly Detection Techniques and Applications 7
- Explainable Artificial Intelligence (XAI) 2
- Natural Language Processing Techniques 1
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- Advanced Neural Network Applications 3
- Co-authors
- Dawn Song (7 shared papers)Jacob Steinhardt (5 shared papers)Steven Basart (5 shared papers)Mantas Mazeika (5 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)International Conference on Learning Representations (2 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)arXiv (Cornell University) (4 papers)
- Partner nations
- United StatesAustraliaSwitzerland
In The Last Decade
Dan Hendrycks
18 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 739
- Health Informatics 33
- Signal Processing 79
- Hardware and Architecture 31
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
| # | Work | ||
|---|---|---|---|
| 1 | The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Hit paper breakdown → | 2021 | 503 |
| 2 | Natural Adversarial Examples Hit paper breakdown → | 2021 | 374 |
| 3 | Measuring Massive Multitask Language Understanding Hit paper breakdown → | 2021 | 182 |
| 4 | 2018 | 112 | |
| 5 | Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty | 2019 | 77 |
| 6 | AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty | 2020 | 61 |
| 7 | AI deception: A survey of examples, risks, and potential solutions Hit paper breakdown → | 2024 | 51 |
| 8 | 2022 | 48 | |
| 9 | Early Methods for Detecting Adversarial Images | 2017 | 47 |
| 10 | A Benchmark for Anomaly Segmentation. | 2019 | 23 |
| 11 | 2019 | 12 | |
| 12 | Visible Progress on Adversarial Images and a New Saliency Map. | 2016 | 10 |
| 13 | 2019 | 7 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 4 | |
| 16 | A Quantitative Measure of Generative Adversarial Network Distributions | 2017 | 2 |
| 17 | Generalizing and Improving Weight Initialization. | 2016 | 1 |
| 18 | CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review | 2021 | 1 |
| 19 | 2024 | 0 |
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 19 papers that have together received 1.5k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (12 papers), Anomaly Detection Techniques and Applications (7 papers), Advanced Malware Detection Techniques (4 papers), Advanced Neural Network Applications (3 papers), Artificial Intelligence in Law (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Natural Language Processing Techniques (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (739 citations), Health Informatics (33 citations), Signal Processing (79 citations) and Hardware and Architecture (31 citations). Dan Hendrycks has collaborated with scholars based in United States, Australia and Switzerland. Frequent co-authors include Dawn Song, Jacob Steinhardt, Steven Basart, Mantas Mazeika, Kevin Zhao, Saurav Kadavath, Justin Gilmer, Norman Mu, Samyak Parajuli and Tyler Zhu. Their work appears in journals such as Patterns, Proceedings of the VLDB Endowment, International Conference on Learning Representations, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).
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.