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Laurens van der Maaten
Laurens van der Maaten
Distinguished Research Scientist, Meta AI
Verified email at meta.com - Homepage
Title
Cited by
Cited by
Year
Densely Connected Convolutional Networks
G Huang, Z Liu, L van der Maaten, KQ Weinberger
IEEE Conference on Computer Vision and Pattern Recognition, 2016
452862016
Visualizing data using t-SNE
L van der Maaten, G Hinton
The Journal of Machine Learning Research 9 (2579-2605), 85, 2008
370422008
Dimensionality reduction: A comparative review
LJP Van der Maaten, EO Postma, HJ Van den Herik
Technical Report TiCC TR 2009-005, 2009
3821*2009
Accelerating t-SNE using Tree-Based Algorithms
L Van Der Maaten
The Journal of Machine Learning Research 15 (1), 3221-3245, 2014
29382014
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
23092017
Countering adversarial images using input transformations
C Guo, M Rana, M Cisse, L Van Der Maaten
arXiv preprint arXiv:1711.00117, 2017
15282017
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
15142018
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
15092018
Self-supervised learning of pretext-invariant representations
I Misra, L Maaten
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
15032020
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
9482019
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
946*2017
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
9432018
Learning a parametric embedding by preserving local structure
L van der Maaten
Proceedings of AI-STATS, 2009
7082009
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
6182017
Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation
JH Krijthe, L Van der Maaten
R package version 0.13, URL https://github. com/jkrijthe/Rtsne, 2015
508*2015
Submanifold sparse convolutional networks
B Graham, L Van der Maaten
arXiv preprint arXiv:1706.01307, 2017
4852017
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
4722019
Learning Visual Features from Large Weakly Supervised Data
A Joulin, L van der Maaten, A Jabri, N Vasilache
European Conference on Computer Vision, 2016
4112016
Simpleshot: Revisiting nearest-neighbor classification for few-shot learning
Y Wang, WL Chao, KQ Weinberger, L Van Der Maaten
arXiv preprint arXiv:1911.04623, 2019
3422019
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
3292016
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