Guillaume Alain
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Media Technology
- Molecular Biology
- Co-authors
- Yoshua BengioPascal VincentLi YaoWa James TamLiang ZhangMathias BerglundLaurent DinhTapani Raiko
- Topics
- Neural Networks and Applications (5 papers)Generative Adversarial Networks and Image Synthesis (4 papers)Model Reduction and Neural Networks (2 papers)
- Journals
- BioinformaticsJournal of Machine Learning ResearchInformation and Inference A Journal of the IMA
- Partner nations
- CanadaFinlandUnited States
In The Last Decade
Guillaume Alain
8 papers receiving 385 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 215
- Artificial Intelligence 186
- Signal Processing 86
- Media Technology 24
- Molecular Biology 21
Countries citing papers authored by Guillaume Alain
This map shows the geographic impact of Guillaume Alain'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 Guillaume Alain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guillaume Alain more than expected).
Fields of papers citing papers by Guillaume Alain
This network shows the impact of papers produced by Guillaume Alain. 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 Guillaume Alain. The network helps show where Guillaume Alain may publish in the future.
Co-authorship network of co-authors of Guillaume Alain
This figure shows the co-authorship network connecting the top 25 collaborators of Guillaume Alain. A scholar is included among the top collaborators of Guillaume Alain 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 Guillaume Alain. Guillaume Alain is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 55 | |
| 3 | Techniques for Learning Binary Stochastic Feedforward Neural Networks | 23 |
| 4 | What Regularized Auto-Encoders Learn from the Data Generating Distribution | 130 |
| 5 | 103 | |
| 6 | Regularized Auto-Encoders Estimate Local Statistics | 3 |
| 7 | 13 | |
| 8 | 65 |
About Guillaume Alain
Guillaume Alain is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 8 papers that have together received 410 indexed citations. Recurring topics across this work include Neural Networks and Applications (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Model Reduction and Neural Networks (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (215 citations), Signal Processing (86 citations) and Artificial Intelligence (186 citations). Guillaume Alain has collaborated with scholars based in Canada, Finland and United States. Frequent co-authors include Yoshua Bengio, Pascal Vincent, Li Yao, Wa James Tam, Liang Zhang, Mathias Berglund, Laurent Dinh, Tapani Raiko, Li Yao and Jason Yosinski. Their work appears in journals such as Bioinformatics, Journal of Machine Learning Research and Information and Inference A Journal of the IMA.
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.