Pascal Lamblin

9.6k total citations · 2 hit papers
9 papers, 1.9k citations indexed

About

Pascal Lamblin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Pascal Lamblin has authored 9 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Hardware and Architecture. Recurrent topics in Pascal Lamblin's work include Parallel Computing and Optimization Techniques (3 papers), Computational Physics and Python Applications (2 papers) and Formal Methods in Verification (1 paper). Pascal Lamblin is often cited by papers focused on Parallel Computing and Optimization Techniques (3 papers), Computational Physics and Python Applications (2 papers) and Formal Methods in Verification (1 paper). Pascal Lamblin collaborates with scholars based in Canada, United States and Sweden. Pascal Lamblin's co-authors include Yoshua Bengio, Jérôme Louradour, Hugo Larochelle, David Warde-Farley, Olivier Breuleux, Frédéric Bastien, Guillaume Desjardins, Razvan Pascanu, James Bergstra and Joseph Turian and has published in prestigious journals such as Journal of Machine Learning Research, Journal on Multimodal User Interfaces and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Pascal Lamblin

9 papers receiving 1.8k citations

Hit Papers

Exploring Strategies for Training Deep Neural Networks 2009 2026 2014 2020 2009 2010 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Exploring Strategies for Training Deep Neural Networks
    2009 758 citations Hugo Larochelle, Yoshua Bengio et al. Journal of Machine Learning Research profile →
  2. Theano: A CPU and GPU Math Compiler in Python
    2010 686 citations James Bergstra, Olivier Breuleux et al. Proceedings of the Python in Science Conferences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pascal Lamblin Canada 7 831 742 282 186 154 9 1.9k
Ashok Krishnamurthy United States 19 921 1.1× 551 0.7× 498 1.8× 248 1.3× 116 0.8× 100 2.0k
Pengjiang Qian China 25 942 1.1× 722 1.0× 182 0.6× 173 0.9× 92 0.6× 101 2.2k
Xuemin Chi China 7 638 0.8× 551 0.7× 575 2.0× 119 0.6× 226 1.5× 14 1.8k
Raman Arora United States 17 1.0k 1.2× 1.0k 1.4× 381 1.4× 74 0.4× 70 0.5× 72 2.1k
Nash Borges United States 6 669 0.8× 527 0.7× 593 2.1× 108 0.6× 221 1.4× 9 1.7k
Fu Jie Huang China 12 1.1k 1.3× 1.5k 2.0× 336 1.2× 82 0.4× 137 0.9× 21 2.6k
Özgür Çetin United States 12 919 1.1× 549 0.7× 780 2.8× 137 0.7× 228 1.5× 27 2.0k
Habiboulaye Amadou Boubacar France 3 798 1.0× 477 0.6× 159 0.6× 49 0.3× 162 1.1× 6 1.8k
Friedhelm Schwenker Germany 30 1.4k 1.6× 828 1.1× 321 1.1× 533 2.9× 205 1.3× 189 3.2k

Countries citing papers authored by Pascal Lamblin

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Pascal Lamblin

This figure shows the co-authorship network connecting the top 25 collaborators of Pascal Lamblin. A scholar is included among the top collaborators of Pascal Lamblin 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 Pascal Lamblin. Pascal Lamblin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Austin, Jacob, Nimesh Ghelani, Pascal Lamblin, et al.. (2024). Resolving Code Review Comments with Machine Learning. 204–215. 6 indexed citations
2.
Chen, Zimin, Vincent J. Hellendoorn, Pascal Lamblin, et al.. (2021). PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair. Neural Information Processing Systems. 34. 12 indexed citations
3.
Bouthillier, Xavier, et al.. (2018). Oríon : Experiment Version Control for Efficient Hyperparameter Optimization. 1 indexed citations
4.
Merriënboer, Bart van, Olivier Breuleux, Arnaud Bergeron, & Pascal Lamblin. (2018). Automatic differentiation in ML: Where we are and where we should be going. arXiv (Cornell University). 31. 8757–8767. 25 indexed citations
5.
Kahou, Samira Ebrahimi, Xavier Bouthillier, Pascal Lamblin, et al.. (2015). EmoNets: Multimodal deep learning approaches for emotion recognition in video. Journal on Multimodal User Interfaces. 10(2). 99–111. 263 indexed citations
6.
Bergstra, James, Frédéric Bastien, Olivier Breuleux, et al.. (2012). Theano: Deep Learning on GPUs with Python. 125 indexed citations
7.
Bergstra, James, Olivier Breuleux, Frédéric Bastien, et al.. (2010). Theano: A CPU and GPU Math Compiler in Python. Proceedings of the Python in Science Conferences. 18–24. 686 indexed citations breakdown →
8.
Larochelle, Hugo, Yoshua Bengio, Jérôme Louradour, & Pascal Lamblin. (2009). Exploring Strategies for Training Deep Neural Networks. Journal of Machine Learning Research. 10(1). 1–40. 758 indexed citations breakdown →
9.
Roux, Nicolas Le, et al.. (2007). Learning the 2-D Topology of Images. HAL (Le Centre pour la Communication Scientifique Directe). 20. 841–848. 8 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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