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Samira Ebrahimi Kahou
Samira Ebrahimi Kahou
Associate Professor, École de technologie supérieure/Mila/Canada CIFAR AI Chair
Zweryfikowany adres z etsmtl.ca - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Fitnets: Hints for thin deep nets
A Romero, N Ballas, SE Kahou, A Chassang, C Gatta, Y Bengio
arXiv preprint arXiv:1412.6550, 2014
24302014
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
1026*2016
The" something something" video database for learning and evaluating visual common sense
R Goyal, S Ebrahimi Kahou, V Michalski, J Materzynska, S Westphal, ...
Proceedings of the IEEE international conference on computer vision, 5842-5850, 2017
6632017
Emonets: Multimodal deep learning approaches for emotion recognition in video
SE Kahou, X Bouthillier, P Lamblin, C Gulcehre, V Michalski, K Konda, ...
Journal on Multimodal User Interfaces 10 (2), 99-111, 2016
4182016
Recurrent neural networks for emotion recognition in video
S Ebrahimi Kahou, V Michalski, K Konda, R Memisevic, C Pal
Proceedings of the 2015 ACM on international conference on multimodal …, 2015
3572015
Combining Modality Specific Deep Neural Networks for Emotion Recognition in Video
SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ...
Proceedings of the 15th ACM on International Conference on Multimodal …, 2013
3552013
Do deep convolutional nets really need to be deep and convolutional?
G Urban, KJ Geras, SE Kahou, O Aslan, S Wang, R Caruana, A Mohamed, ...
arXiv preprint arXiv:1603.05691, 2016
2072016
Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
E Racah, C Beckham, T Maharaj, S Ebrahimi Kahou, M Prabhat, C Pal
Advances in neural information processing systems 30, 2017
1662017
Towards deep conversational recommendations
R Li, S Ebrahimi Kahou, H Schulz, V Michalski, L Charlin, C Pal
Advances in neural information processing systems 31, 2018
1652018
Figureqa: An annotated figure dataset for visual reasoning
SE Kahou, V Michalski, A Atkinson, Á Kádár, A Trischler, Y Bengio
arXiv preprint arXiv:1710.07300, 2017
1142017
Ratm: Recurrent attentive tracking model
S Ebrahimi Kahou, V Michalski, R Memisevic, C Pal, P Vincent
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
100*2017
Chatpainter: Improving text to image generation using dialogue
S Sharma, D Suhubdy, V Michalski, SE Kahou, Y Bengio
arXiv preprint arXiv:1802.08216, 2018
802018
Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction
A El-Nouby, S Sharma, H Schulz, D Hjelm, LE Asri, SE Kahou, Y Bengio, ...
Proceedings of the IEEE International Conference on Computer Vision, 10304-10312, 2019
70*2019
Deep-hurricane-tracker: Tracking and forecasting extreme climate events
S Kim, H Kim, J Lee, S Yoon, SE Kahou, K Kashinath, M Prabhat
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 1761-1769, 2019
672019
Highres-net: Recursive fusion for multi-frame super-resolution of satellite imagery
M Deudon, A Kalaitzis, I Goytom, MR Arefin, Z Lin, K Sankaran, ...
arXiv preprint arXiv:2002.06460, 2020
56*2020
Facial Expression Analysis Based on High Dimensional Binary Features
SE Kahou, P Froumenty, C Pal
Computer Vision - ECCV 2014 Workshops, Part II, 135-147, 2015
432015
Towards non-saturating recurrent units for modelling long-term dependencies
S Chandar, C Sankar, E Vorontsov, SE Kahou, Y Bengio
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3280-3287, 2019
412019
Do deep convolutional nets really need to be deep (or even convolutional)?
G Urban, KJ Geras, SE Kahou, OAS Wang, R Caruana, A Mohamed, ...
372016
Accounting for variance in machine learning benchmarks
X Bouthillier, P Delaunay, M Bronzi, A Trofimov, B Nichyporuk, J Szeto, ...
Proceedings of Machine Learning and Systems 3, 747-769, 2021
352021
Segmenting and tracking extreme climate events using neural networks
M Mudigonda, S Kim, A Mahesh, S Kahou, K Kashinath, D Williams, ...
Deep Learning for Physical Sciences (DLPS) Workshop, held with NIPS Conference, 2017
262017
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