Pascal Lamblin
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- Generative Adversarial Networks and Image Synthesis 1
- Signal Processing top 2%
- Artificial Intelligence top 2%
- Computational Physics and Python Applications 2
- Algorithms and Data Compression 1
- Machine Learning and Algorithms 1
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- Emotion and Mood Recognition 1
- Media Technology top 5%
- Image Processing Techniques and Applications 1
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- Parallel Computing and Optimization Techniques 3
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- Software Engineering Research 1
- Co-authors
- Yoshua BengioHugo LarochelleJérôme LouradourDavid Warde-FarleyOlivier BreuleuxRazvan PascanuJames BergstraGuillaume Desjardins
- Journals
- Journal of Machine Learning Research (1 paper)Journal on Multimodal User Interfaces (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- CanadaUnited StatesSweden
In The Last Decade
Pascal Lamblin
9 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 742
- Signal Processing 282
- Artificial Intelligence 831
- Experimental and Cognitive Psychology 186
- Media Technology 100
Countries citing papers authored by Pascal Lamblin
This map shows the geographic impact of Pascal Lamblin'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 Pascal Lamblin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Lamblin more than expected).
Fields of papers citing papers by Pascal Lamblin
This network shows the impact of papers produced by Pascal Lamblin. 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 Pascal Lamblin. The network helps show where Pascal Lamblin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Pascal Lamblin, 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 | 2024 | 6 | |
| 2 | PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair | 2021 | 12 |
| 3 | Oríon : Experiment Version Control for Efficient Hyperparameter Optimization | 2018 | 1 |
| 4 | 2018 | 25 | |
| 5 | 2015 | 263 | |
| 6 | Theano: Deep Learning on GPUs with Python | 2012 | 125 |
| 7 | Theano: A CPU and GPU Math Compiler in Pythonbreakdown → | 2010 | 686 |
| 8 | Exploring Strategies for Training Deep Neural Networksbreakdown → | 2009 | 758 |
| 9 | Learning the 2-D Topology of Images | 2007 | 8 |
About Pascal Lamblin
Pascal Lamblin is a scholar working on Hardware and Architecture, Software and Artificial Intelligence, having authored 9 papers that have together received 1.9k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (3 papers), Computational Physics and Python Applications (2 papers), Image Processing Techniques and Applications (1 paper), Algorithms and Data Compression (1 paper), Emotion and Mood Recognition (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper), Machine Learning and Algorithms (1 paper) and Software Engineering Research (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (742 citations), Signal Processing (282 citations) and Artificial Intelligence (831 citations). Pascal Lamblin has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Yoshua Bengio, Hugo Larochelle, Jérôme Louradour, David Warde-Farley, Olivier Breuleux, Razvan Pascanu, James Bergstra, Guillaume Desjardins, Frédéric Bastien and Joseph Turian. Their work appears in journals such as Journal of Machine Learning Research, Journal on Multimodal User Interfaces, HAL (Le Centre pour la Communication Scientifique Directe), arXiv (Cornell University) and Neural Information Processing Systems.
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.