Joost van Amersfoort
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- Adversarial Robustness in Machine Learning 3
- Anomaly Detection Techniques and Applications 3
- Machine Learning and Data Classification 1
- Machine Learning and Algorithms 1
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- Functional Brain Connectivity Studies 1
- Neural dynamics and brain function 1
- EEG and Brain-Computer Interfaces 1
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- Fault Detection and Control Systems 2
- Co-authors
- Yarin GalAndreas KirschJishnu MukhotiPhilip H. S. TorrLewis SmithYee Whye TehAndrew J. QuinnUsama Pervaiz
- Partner nations
- United KingdomSwitzerland
In The Last Decade
Joost van Amersfoort
6 papers receiving 120 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 89
- Health Informatics 2
- Computer Vision and Pattern Recognition 22
- Cognitive Neuroscience 17
- Management Science and Operations Research 9
Countries citing papers authored by Joost van Amersfoort
This map shows the geographic impact of Joost van Amersfoort'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 Joost van Amersfoort with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joost van Amersfoort more than expected).
Fields of papers citing papers by Joost van Amersfoort
This network shows the impact of papers produced by Joost van Amersfoort. 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 Joost van Amersfoort. The network helps show where Joost van Amersfoort may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Joost van Amersfoort, 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 | 2023 | 41 | |
| 2 | 2022 | 17 | |
| 3 | Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression. | 2021 | 7 |
| 4 | Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network | 2020 | 9 |
| 5 | Uncertainty Estimation Using a Single Deep Deterministic Neural Network | 2020 | 14 |
| 6 | BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning | 2019 | 38 |
About Joost van Amersfoort
Joost van Amersfoort is a scholar working on Artificial Intelligence, Control and Systems Engineering and Cognitive Neuroscience, having authored 6 papers that have together received 126 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Anomaly Detection Techniques and Applications (3 papers), Fault Detection and Control Systems (2 papers), Functional Brain Connectivity Studies (1 paper), Machine Learning and Data Classification (1 paper), Neural dynamics and brain function (1 paper), Machine Learning and Algorithms (1 paper) and EEG and Brain-Computer Interfaces (1 paper). The work is most often cited by research in Artificial Intelligence (89 citations), Health Informatics (2 citations) and Computer Vision and Pattern Recognition (22 citations). Joost van Amersfoort has collaborated with scholars based in United Kingdom and Switzerland. Frequent co-authors include Yarin Gal, Andreas Kirsch, Jishnu Mukhoti, Philip H. S. Torr, Lewis Smith, Yee Whye Teh, Andrew J. Quinn, Usama Pervaiz, Pascal Notin and Mark W. Woolrich.
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.