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Dumitru Erhan
Dumitru Erhan
Director of Research @ Google DeepMind
Bestätigte E-Mail-Adresse bei google.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
553072015
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
355082016
Intriguing properties of neural networks
C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ...
arXiv preprint arXiv:1312.6199, 2013
149492013
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
70352015
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
34102010
Deep neural networks for object detection
C Szegedy, A Toshev, D Erhan
Advances in neural information processing systems 26, 1-9, 2013
19442013
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
17422013
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
17342017
Visualizing higher-layer features of a deep network
D Erhan, Y Bengio, A Courville, P Vincent
University of Montreal 1341 (3), 1, 2009
15762009
Domain separation networks
K Bousmalis, G Trigeorgis, N Silberman, D Krishnan, D Erhan
Advances in neural information processing systems 29, 2016
15132016
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
15012014
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
13552007
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
10772014
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
1076*2016
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
10002016
Model-based reinforcement learning for atari
L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ...
arXiv preprint arXiv:1903.00374, 2019
7862019
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
6232019
The difficulty of training deep architectures and the effect of unsupervised pre-training
D Erhan, PA Manzagol, Y Bengio, S Bengio, P Vincent
Artificial intelligence and statistics, 153-160, 2009
6172009
Zero-data learning of new tasks.
H Larochelle, D Erhan, Y Bengio
AAAI 1 (2), 3, 2008
5972008
A benchmark for interpretability methods in deep neural networks
S Hooker, D Erhan, PJ Kindermans, B Kim
Advances in neural information processing systems 32, 2019
5622019
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