Följ
Dumitru Erhan
Dumitru Erhan
Director of Research @ Google DeepMind
Verifierad e-postadress på google.com - Startsida
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Going deeper with convolutions
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
658662015
Ssd: Single shot multibox detector
W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
453072016
Intriguing properties of neural networks
C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ...
arXiv preprint arXiv:1312.6199, 2013
190992013
Show and tell: A neural image caption generator
O Vinyals, A Toshev, S Bengio, D Erhan
Proceedings of the IEEE conference on computer vision and pattern …, 2015
81932015
Why does unsupervised pre-training help deep learning?
D Erhan, A Courville, Y Bengio, P Vincent
Proceedings of the thirteenth international conference on artificial …, 2010
37162010
Challenges in representation learning: A report on three machine learning contests
IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ...
Neural information processing: 20th international conference, ICONIP 2013 …, 2013
23232013
Deep neural networks for object detection
C Szegedy, A Toshev, D Erhan
Advances in neural information processing systems 26, 1-9, 2013
21862013
Unsupervised pixel-level domain adaptation with generative adversarial networks
K Bousmalis, N Silberman, D Dohan, D Erhan, D Krishnan
Proceedings of the IEEE conference on computer vision and pattern …, 2017
19972017
Visualizing higher-layer features of a deep network
D Erhan, Y Bengio, A Courville, P Vincent
University of Montreal 1341 (3), 1, 2009
18762009
Domain separation networks
K Bousmalis, G Trigeorgis, N Silberman, D Krishnan, D Erhan
Advances in neural information processing systems 29, 2016
18442016
Scalable object detection using deep neural networks
D Erhan, C Szegedy, A Toshev, D Anguelov
Proceedings of the IEEE conference on computer vision and pattern …, 2014
16402014
An empirical evaluation of deep architectures on problems with many factors of variation
H Larochelle, D Erhan, A Courville, J Bergstra, Y Bengio
Proceedings of the 24th international conference on Machine learning, 473-480, 2007
14562007
Training deep neural networks on noisy labels with bootstrapping
S Reed, H Lee, D Anguelov, C Szegedy, D Erhan, A Rabinovich
arXiv preprint arXiv:1412.6596, 2014
12582014
Show and tell: Lessons learned from the 2015 mscoco image captioning challenge
O Vinyals, A Toshev, S Bengio, D Erhan
IEEE transactions on pattern analysis and machine intelligence 39 (4), 652-663, 2016
11572016
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
1142*2016
Model-based reinforcement learning for atari
L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ...
arXiv preprint arXiv:1903.00374, 2019
10912019
Proceedings of the IEEE conference on computer vision and pattern recognition
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ...
Going deeper with convolutions, 1-9, 2015
9912015
SSD: single shot MultiBox detector
A LIUW, D Erhan
European conference on computer vision, 21-37, 2016
9102016
Leibe B, Matas J, Sebe N, Welling M, et al. SSD: single shot multibox detector
W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg
Computer Vision–ECCV 2016, 21-37, 2016
8562016
The (un) reliability of saliency methods
PJ Kindermans, S Hooker, J Adebayo, M Alber, KT Schütt, S Dähne, ...
Explainable AI: Interpreting, explaining and visualizing deep learning, 267-280, 2019
8472019
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Artiklar 1–20