Jean Kossaifi

29 papers receiving 2.4k citations

Hit Papers

Machine learning for neuroimaging with scikit-learn2014202620182022201420244008001.2k

Peers

Jean Kossaifi
Comparison fields: 5 of 189
  • Cognitive Neuroscience 861
  • Computer Vision and Pattern Recognition 570
  • Experimental and Cognitive Psychology 467
  • Artificial Intelligence 381
  • Radiology, Nuclear Medicine and Imaging 318
Replace Fengyu Cong with:
Fengyu Cong China
Jinbo Bi United States
Hans Knutsson Sweden
Nathan Intrator Israel
Robert Tibshirani United States
Lewis D. Griffin United Kingdom
Jingu Kim South Korea
Morten Mørup Denmark
David R. Hardoon United Kingdom
Paul Sajda United States
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Citations per field
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Fengyu Cong · 1×
Citations per year

Countries citing papers authored by Jean Kossaifi

Since Specialization
Citations

This map shows the geographic impact of Jean Kossaifi'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 Jean Kossaifi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean Kossaifi more than expected).

Fields of papers citing papers by Jean Kossaifi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean Kossaifi. 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 Jean Kossaifi. The network helps show where Jean Kossaifi may publish in the future.

Co-authorship network of co-authors of Jean Kossaifi

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2
Neural operators for accelerating scientific simulations and designbreakdown →
90
3 4
4 6
5 77
6 127
7
Convolutional Tensor-Train LSTM for Spatio-temporal Learning
5
8 21
9
Efficient N-Dimensional Convolutions via Higher-Order Factorization
2
10
Stochastically Rank-Regularized Tensor Regression Networks.
2
11 11
12 20
13
Defensive Tensorization: Randomized Tensor Parametrization for Robust Neural Networks
1
14 157
15
Robust Conditional Generative Adversarial Networks
1
16 129
17 9
18 8
19 189
20
Machine learning for neuroimaging with scikit-learnbreakdown →
1364

About Jean Kossaifi

Jean Kossaifi is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 29 papers that have together received 2.4k indexed citations. Recurring topics across this work include Tensor decomposition and applications (13 papers), Face recognition and analysis (8 papers) and Advanced Neural Network Applications (6 papers). The work is most often cited by research in Computational Mathematics (134 citations), Cognitive Neuroscience (861 citations) and Experimental and Cognitive Psychology (467 citations). Jean Kossaifi has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Philippe Gervais, Gaël Varoquaux, Alexandre Gramfort, Fabian Pedregosa, Maja Pantić, Michael Eickenberg, Andreas Mueller, Alexandre Abraham, Bertrand Thirion and Georgios Tzimiropoulos. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and IEEE Transactions on Image Processing.

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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