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Laurens van der Maaten
Laurens van der Maaten
Research Director, Meta AI (FAIR)
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Title
Cited by
Cited by
Year
Visualizing data using t-SNE
L van der Maaten, G Hinton
The Journal of Machine Learning Research 9 (2579-2605), 85, 2008
360312008
Densely Connected Convolutional Networks
G Huang, Z Liu, L van der Maaten, KQ Weinberger
IEEE Conference on Computer Vision and Pattern Recognition, 2016
352542016
Dimensionality reduction: A comparative review
LJP Van der Maaten, EO Postma, HJ Van den Herik
Technical Report TiCC TR 2009-005, 2009
3415*2009
Accelerating t-SNE using Tree-Based Algorithms
L Van Der Maaten
The Journal of Machine Learning Research 15 (1), 3221-3245, 2014
25632014
Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
J Johnson, B Hariharan, L Van Der Maaten, L Fei-Fei, C Lawrence Zitnick, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
18322017
Exploring the limits of weakly supervised pretraining
D Mahajan, R Girshick, V Ramanathan, K He, M Paluri, Y Li, A Bharambe, ...
Proceedings of the European conference on computer vision (ECCV), 181-196, 2018
12302018
Countering adversarial images using input transformations
C Guo, M Rana, M Cisse, L Van Der Maaten
arXiv preprint arXiv:1711.00117, 2017
12202017
Self-supervised learning of pretext-invariant representations
I Misra, L Maaten
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
11132020
3d semantic segmentation with submanifold sparse convolutional networks
B Graham, M Engelcke, L Van Der Maaten
Proceedings of the IEEE conference on computer vision and pattern …, 2018
10922018
Feature denoising for improving adversarial robustness
C Xie, Y Wu, L Maaten, AL Yuille, K He
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
7832019
Condensenet: An efficient densenet using learned group convolutions
G Huang, S Liu, L Van der Maaten, KQ Weinberger
Proceedings of the IEEE conference on computer vision and pattern …, 2018
7802018
Multi-scale dense networks for resource efficient image classification
G Huang, D Chen, T Li, F Wu, L Van Der Maaten, KQ Weinberger
arXiv preprint arXiv:1703.09844, 2017
733*2017
Learning a parametric embedding by preserving local structure
L van der Maaten
Proceedings of AI-STATS, 2009
6322009
Inferring and executing programs for visual reasoning
J Johnson, B Hariharan, L Van Der Maaten, J Hoffman, L Fei-Fei, ...
Proceedings of the IEEE international conference on computer vision, 2989-2998, 2017
5342017
Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation
JH Krijthe
R package version 0.13, URL https://github. com/jkrijthe/Rtsne, 2015
4092015
Submanifold sparse convolutional networks
B Graham, L Van der Maaten
arXiv preprint arXiv:1706.01307, 2017
3592017
Learning Visual Features from Large Weakly Supervised Data
A Joulin, L van der Maaten, A Jabri, N Vasilache
European Conference on Computer Vision, 2016
3422016
Convolutional networks with dense connectivity
G Huang, Z Liu, G Pleiss, L Van Der Maaten, KQ Weinberger
IEEE transactions on pattern analysis and machine intelligence 44 (12), 8704 …, 2019
3122019
Revisiting visual question answering baselines
A Jabri, A Joulin, L Van Der Maaten
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
2962016
Approximated and user steerable tSNE for progressive visual analytics
N Pezzotti, BPF Lelieveldt, L Van Der Maaten, T Höllt, E Eisemann, ...
IEEE transactions on visualization and computer graphics 23 (7), 1739-1752, 2016
2952016
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