Alex Lamb
Impact in
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Adversarial Robustness in Machine Learning
- Natural Language Processing Techniques
- Anomaly Detection Techniques and Applications
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
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- Adversarial Robustness in Machine Learning 8
- Anomaly Detection Techniques and Applications 7
- Domain Adaptation and Few-Shot Learning 5
- Topic Modeling 4
- Neural Networks and Applications 3
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- Generative Adversarial Networks and Image Synthesis 4
- Image Processing and 3D Reconstruction 3
- Handwritten Text Recognition Techniques 2
- Co-authors
- Yoshua Bengio (14 shared papers)Mark Dredze (2 shared papers)Michael J. Paul (2 shared papers)Christopher Beckham (5 shared papers)Ioannis Mitliagkas (4 shared papers)Aaron Courville (3 shared papers)Amir Najafi (2 shared papers)Vikas Verma (9 shared papers)
- Journals
- Journal of Theoretical Biology (1 paper)Neural Networks (1 paper)SN Computer Science (1 paper)Frontiers in artificial intelligence and applications (1 paper)PolyPublie (École Polytechnique de Montréal) (2 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Alex Lamb
22 papers receiving 833 citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 550
- Computer Vision and Pattern Recognition 337
- Modeling and Simulation 21
- Epidemiology 114
- Signal Processing 42
Countries citing papers authored by Alex Lamb
This map shows the geographic impact of Alex Lamb'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 Alex Lamb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Lamb more than expected).
Fields of papers citing papers by Alex Lamb
This network shows the impact of papers produced by Alex Lamb. 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 Alex Lamb. The network helps show where Alex Lamb may publish in the future.
Co-authors
The 25 scholars most cited alongside Alex Lamb, 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 | 2018 | 242 | |
| 2 | Separating Fact from Fear: Tracking Flu Infections on Twitter | 2013 | 201 |
| 3 | 2016 | 158 | |
| 4 | 2021 | 67 | |
| 5 | 2019 | 37 | |
| 6 | 2019 | 29 | |
| 7 | GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning | 2019 | 25 |
| 8 | 2012 | 22 | |
| 9 | Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. | 2018 | 21 |
| 10 | 2022 | 12 | |
| 11 | Manifold Mixup: Learning Better Representations by Interpolating Hidden States | 2018 | 12 |
| 12 | 2020 | 11 | |
| 13 | Adversarial Mixup Resynthesizers | 2019 | 9 |
| 14 | Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics. | 2012 | 7 |
| 15 | 2020 | 7 | |
| 16 | 2019 | 6 | |
| 17 | 2020 | 5 | |
| 18 | WVU NLP Class Participation in ShARe/CLEF Challenge. | 2013 | 3 |
| 19 | State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations | 2019 | 1 |
| 20 | 2023 | 1 |
About Alex Lamb
Alex Lamb is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Statistical and Nonlinear Physics and Epidemiology, having authored 23 papers that have together received 878 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (7 papers), Domain Adaptation and Few-Shot Learning (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Topic Modeling (4 papers), Neural Networks and Applications (3 papers), Image Processing and 3D Reconstruction (3 papers) and Handwritten Text Recognition Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (550 citations), Computer Vision and Pattern Recognition (337 citations), Modeling and Simulation (21 citations), Epidemiology (114 citations) and Signal Processing (42 citations). Alex Lamb has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Yoshua Bengio, Mark Dredze, Michael J. Paul, Christopher Beckham, Ioannis Mitliagkas, Aaron Courville, Amir Najafi, Vikas Verma, David López-Paz and Vikas Verma. Their work appears in journals such as Journal of Theoretical Biology, Neural Networks, SN Computer Science, Frontiers in artificial intelligence and applications and PolyPublie (École Polytechnique de Montréal).
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.