Vincent Michalski
Vincent Michalski
Ph.D. candidate at Université de Montréal
Verified email at - Homepage
Cited by
Cited by
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
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
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, 99-111, 2016
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
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
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
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
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
Modeling Deep Temporal Dependencies with Recurrent "Grammar Cells"
V Michalski, R Memisevic, K Konda
Advances in neural information processing systems, 1925-1933, 2014
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
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
Chatpainter: Improving text to image generation using dialogue
S Sharma, D Suhubdy, V Michalski, SE Kahou, Y Bengio
arXiv preprint arXiv:1802.08216, 2018
Multi-image super-resolution for remote sensing using deep recurrent networks
MR Arefin, V Michalski, PL St-Charles, A Kalaitzis, S Kim, SE Kahou, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
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
The role of spatio-temporal synchrony in the encoding of motion.
KR Konda, R Memisevic, V Michalski
ICLR (Poster), 2014
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
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
Learning robust dynamics through variational sparse gating
AK Jain, S Sujit, S Joshi, V Michalski, D Hafner, S Ebrahimi Kahou
Advances in neural information processing systems 35, 1612-1626, 2022
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, ...
AGU Fall Meeting Abstracts 2017, IN11E-06, 2017
Neural Networks for Motion Understanding
V Michalski
Department for Computer Science, Goethe-University Frankfurt, 2013
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