Alex Lamb

3.3k total citations
21 papers, 745 citations indexed

About

Alex Lamb is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Sociology and Political Science. According to data from OpenAlex, Alex Lamb has authored 21 papers receiving a total of 745 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 3 papers in Sociology and Political Science. Recurrent topics in Alex Lamb's work include Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (7 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Alex Lamb is often cited by papers focused on Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (7 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Alex Lamb collaborates with scholars based in United States, Canada and Finland. Alex Lamb's co-authors include Yoshua Bengio, Mark Dredze, Michael J. Paul, Aaron Courville, Christopher Beckham, Vikas Verma, Ioannis Mitliagkas, Anirudh Goyal, Ying Zhang and Saizheng Zhang and has published in prestigious journals such as Journal of Theoretical Biology, Neural Networks and SN Computer Science.

In The Last Decade

Alex Lamb

20 papers receiving 700 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Alex Lamb United States	11	472	273	106	87	42	21	745
Shucheng Huang China	12	316 0.7×	301 1.1×	21 0.2×	109 1.3×	57 1.4×	51	715
Ludovic Denoyer France	15	853 1.8×	263 1.0×	57 0.5×	14 0.2×	78 1.9×	34	1.1k
Luca Rossi United Kingdom	13	284 0.6×	130 0.5×	26 0.2×	61 0.7×	7 0.2×	38	502
NhatHai Phan United States	12	461 1.0×	121 0.4×	20 0.2×	84 1.0×	8 0.2×	37	661
Chao Huang China	14	422 0.9×	360 1.3×	38 0.4×	18 0.2×	35 0.8×	55	727
Katayoun Farrahi United Kingdom	15	126 0.3×	188 0.7×	85 0.8×	71 0.8×	10 0.2×	37	816
David Albrecht Australia	12	430 0.9×	121 0.4×	22 0.2×	35 0.4×	20 0.5×	48	735
Shishir Kumar India	14	275 0.6×	145 0.5×	39 0.4×	88 1.0×	19 0.5×	83	787
Arun Chauhan United States	14	252 0.5×	125 0.5×	15 0.1×	37 0.4×	88 2.1×	68	622

Countries citing papers authored by Alex Lamb

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Alex Lamb

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Lamb. A scholar is included among the top collaborators of Alex Lamb based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alex Lamb. Alex Lamb is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Liu, Dianbo, Alex Lamb, Ji Xu, et al.. (2023). Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8825–8833.

Lamb, Alex, Vikas Verma, Kenji Kawaguchi, et al.. (2022). Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks. 154. 218–233. 11 indexed citations

Liu, Dianbo, Alex Lamb, Kenji Kawaguchi, et al.. (2021). Discrete-Valued Neural Communication in Structured Architectures Enhances Generalization. 1 indexed citations

Verma, Vikas, Meng Qu, Kenji Kawaguchi, et al.. (2021). GraphMix: Improved Training of GNNs for Semi-Supervised Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 35(11). 10024–10032. 61 indexed citations

Lamb, Alex, Sherjil Ozair, Vikas Verma, & David Ha. (2020). SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. 17. 952–961. 5 indexed citations

Lamb, Alex, Tarin Clanuwat, & Asanobu Kitamoto. (2020). KuroNet: Regularized Residual U-Nets for End-to-End Kuzushiji Character Recognition. SN Computer Science. 1(3). 7 indexed citations

Lamb, Alex, Jonathan Binas, Anirudh Goyal, et al.. (2019). State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. International Conference on Machine Learning. 3622–3631. 1 indexed citations

Beckham, Christopher, Sina Honari, Alex Lamb, et al.. (2019). Adversarial Mixup Resynthesizers. PolyPublie (École Polytechnique de Montréal). 9 indexed citations

Verma, Vikas, Meng Qu, Alex Lamb, et al.. (2019). GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. 22 indexed citations

10.

Clanuwat, Tarin, Alex Lamb, & Asanobu Kitamoto. (2019). KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning. 607–614. 28 indexed citations

11.

Beckham, Christopher, Sina Honari, Vikas Verma, et al.. (2019). On Adversarial Mixup Resynthesis. PolyPublie (École Polytechnique de Montréal). 32. 4346–4357. 5 indexed citations

12.

Lamb, Alex, Vikas Verma, Juho Kannala, & Yoshua Bengio. (2019). Interpolated Adversarial Training. Aaltodoc (Aalto University). 95–103. 26 indexed citations

13.

Verma, Vikas, Alex Lamb, Christopher Beckham, et al.. (2018). Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer.. arXiv (Cornell University). 19 indexed citations

14.

Verma, Vikas, Alex Lamb, Christopher Beckham, et al.. (2018). Manifold Mixup: Better Representations by Interpolating Hidden States. arXiv (Cornell University). 6438–6447. 179 indexed citations

15.

Verma, Vikas, Alex Lamb, Christopher Beckham, et al.. (2018). Manifold Mixup: Learning Better Representations by Interpolating Hidden States. 11 indexed citations

16.

Lamb, Alex, Anirudh Goyal, Ying Zhang, et al.. (2016). Professor Forcing: A New Algorithm for Training Recurrent Networks. arXiv (Cornell University). 29. 4601–4609. 150 indexed citations

17.

Jagannathan, V., et al.. (2013). WVU NLP Class Participation in ShARe/CLEF Challenge.. CLEF (Working Notes). 1 indexed citations

18.

Lamb, Alex, Michael J. Paul, & Mark Dredze. (2013). Separating Fact from Fear: Tracking Flu Infections on Twitter. 789–795. 176 indexed citations

19.

Laidre, Mark E., et al.. (2012). Making sense of information in noisy networks: Human communication, gossip, and distortion. Journal of Theoretical Biology. 317. 152–160. 21 indexed citations

20.

Lamb, Alex, Michael J. Paul, & Mark Dredze. (2012). Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics.. 5 indexed citations

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.

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