| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv, arXiv: 1605.02688, 2016 | 787* | 2016 |
| 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 | 312 | 2016 |
| The "Something Something" Video Database for Learning and Evaluating Visual Common Sense. R Goyal, SE Kahou, V Michalski, J Materzynska, S Westphal, H Kim, ... ICCV 1 (2), 3, 2017 | 258 | 2017 |
| 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 | 241 | 2015 |
| A deep reinforcement learning chatbot IV Serban, C Sankar, M Germain, S Zhang, Z Lin, S Subramanian, T Kim, ... arXiv preprint arXiv:1709.02349, 2017 | 171 | 2017 |
| Modeling Deep Temporal Dependencies with Recurrent "Grammar Cells" V Michalski, R Memisevic, K Konda Advances in neural information processing systems, 1925-1933, 2014 | 103 | 2014 |
| 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 | 79* | 2017 |
| Towards deep conversational recommendations R Li, S Ebrahimi Kahou, H Schulz, V Michalski, L Charlin, C Pal Advances in neural information processing systems 31, 9725-9735, 2018 | 58 | 2018 |
| 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 | 55 | 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 | 53 | 2018 |
| The role of spatio-temporal synchrony in the encoding of motion. KR Konda, R Memisevic, V Michalski ICLR (Poster), 2014 | 24* | 2014 |
| 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 | 16 | 2017 |
| A deep reinforcement learning chatbot (short version) IV Serban, C Sankar, M Germain, S Zhang, Z Lin, S Subramanian, T Kim, ... arXiv preprint arXiv:1801.06700, 2018 | 11 | 2018 |
| The octopus approach to the Alexa competition: A deep ensemble-based socialbot IV Serban, C Sankar, S Zhang, Z Lin, S Subramanian, T Kim, S Chandar, ... Alexa Prize Proceedings, 2017 | 11 | 2017 |
| 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 | 4 | 2020 |
| Neural Networks for Motion Understanding V Michalski Department for Computer Science, Goethe-University Frankfurt, 2013 | 3 | 2013 |
| HighRes-net: Multi-Frame Super-Resolution by Recursive Fusion M Deudon, A Kalaitzis, MR Arefin, I Goytom, Z Lin, K Sankaran, ... | 2 | 2019 |
| Assessing uncertainty in deep learning techniques that identify atmospheric rivers in climate simulations A Mahesh, M Mudigonda, SK Kim, K Kashinath, S Kahou, V Michalski, ... AGUFM 2017, IN11E-06, 2017 | 2 | 2017 |
| Multi-Image Super-Resolution for Remote Sensing Using Deep Recurrent Networks M Rifat Arefin, V Michalski, PL St-Charles, A Kalaitzis, S Kim, SE Kahou, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 1 | 2020 |
| An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation V Michalski, V Voleti, SE Kahou, A Ortiz, P Vincent, C Pal, D Precup arXiv preprint arXiv:1908.00061, 2019 | 1 | 2019 |
Samira Ebrahimi KahouAssociate Professor, École de technologie supérieure/MilaVerified email at etsmtl.ca
