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
- Advanced Graph Neural Networks
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- Multimodal Machine Learning Applications
- Advanced Neural Network 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 3
- Neural Networks and Applications 3
- Natural Language Processing Techniques 2
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- Generative Adversarial Networks and Image Synthesis 4
- Image Processing and 3D Reconstruction 3
- Co-authors
- Yoshua Bengio (13 shared papers)Mark Dredze (2 shared papers)Michael J. Paul (2 shared papers)Aaron Courville (3 shared papers)Christopher Beckham (5 shared papers)Vikas Verma (9 shared papers)Ioannis Mitliagkas (4 shared papers)Anirudh Goyal (4 shared papers)
- Journals
- Journal of Theoretical Biology (1 paper)Neural Networks (1 paper)SN Computer Science (1 paper)Aaltodoc (Aalto University) (1 paper)CLEF (Working Notes) (1 paper)
- Partner nations
- United StatesCanadaFinland
In The Last Decade
Alex Lamb
20 papers receiving 700 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 472
- Computer Vision and Pattern Recognition 273
- Modeling and Simulation 24
- Signal Processing 38
- Epidemiology 106
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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 179 | |
| 2 | Separating Fact from Fear: Tracking Flu Infections on Twitter | 2013 | 176 |
| 3 | 2016 | 150 | |
| 4 | 2021 | 61 | |
| 5 | 2019 | 28 | |
| 6 | 2019 | 26 | |
| 7 | GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning | 2019 | 22 |
| 8 | 2012 | 21 | |
| 9 | Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. | 2018 | 19 |
| 10 | 2022 | 11 | |
| 11 | Manifold Mixup: Learning Better Representations by Interpolating Hidden States | 2018 | 11 |
| 12 | Adversarial Mixup Resynthesizers | 2019 | 9 |
| 13 | 2020 | 7 | |
| 14 | 2020 | 7 | |
| 15 | 2020 | 5 | |
| 16 | Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics. | 2012 | 5 |
| 17 | 2019 | 5 | |
| 18 | State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations | 2019 | 1 |
| 19 | WVU NLP Class Participation in ShARe/CLEF Challenge. | 2013 | 1 |
| 20 | Discrete-Valued Neural Communication in Structured Architectures Enhances Generalization | 2021 | 1 |
About Alex Lamb
Alex Lamb is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Epidemiology and Electrical and Electronic Engineering, having authored 21 papers that have together received 745 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 (3 papers), Image Processing and 3D Reconstruction (3 papers), Neural Networks and Applications (3 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (472 citations), Computer Vision and Pattern Recognition (273 citations), Modeling and Simulation (24 citations), Signal Processing (38 citations) and Epidemiology (106 citations). Alex Lamb has collaborated with scholars based in United States, Canada and Finland. Frequent co-authors include Yoshua Bengio, Mark Dredze, Michael J. Paul, Aaron Courville, Christopher Beckham, Vikas Verma, Ioannis Mitliagkas, Anirudh Goyal, Saizheng Zhang and Ying Zhang. Their work appears in journals such as Journal of Theoretical Biology, Neural Networks, SN Computer Science, Aaltodoc (Aalto University) and CLEF (Working Notes).
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.