| On Using Very Large Target Vocabulary for Neural Machine Translation S Jean, K Cho, R Memisevic, Y Bengio ACL 2015, 2014 | 1086 | 2014 |
| 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 | 892 | 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 | 871 | 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 | 447 | 2016 |
| Neural networks with few multiplications Z Lin, M Courbariaux, R Memisevic, Y Bengio arXiv preprint arXiv:1510.03009, 2015 | 384 | 2015 |
| 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 | 381 | 2013 |
| 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 | 378 | 2015 |
| Learning to represent spatial transformations with factored higher-order Boltzmann machines R Memisevic, GE Hinton Neural computation 22 (6), 1473-1492, 2010 | 311 | 2010 |
| Unsupervised learning of image transformations R Memisevic, G Hinton 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 249 | 2007 |
| Generating images with recurrent adversarial networks DJ Im, CD Kim, H Jiang, R Memisevic arXiv preprint arXiv:1602.05110, 2016 | 245 | 2016 |
| Theano: A Python framework for fast computation of mathematical expressions TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ... arXiv preprint arXiv:1605.02688, 2016 | 189 | 2016 |
| Learning visual odometry with a convolutional network. KR Konda, R Memisevic VISAPP (1) 2015, 486-490, 2015 | 178 | 2015 |
| Architectural complexity measures of recurrent neural networks S Zhang, Y Wu, T Che, Z Lin, R Memisevic, RR Salakhutdinov, Y Bengio Advances in neural information processing systems 29, 2016 | 175 | 2016 |
| Denoising criterion for variational auto-encoding framework D Im Im, S Ahn, R Memisevic, Y Bengio Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 171 | 2017 |
| The jester dataset: A large-scale video dataset of human gestures J Materzynska, G Berger, I Bax, R Memisevic Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 164 | 2019 |
| Montreal neural machine translation systems for WMT’15 S Jean, O Firat, K Cho, R Memisevic, Y Bengio Proceedings of the tenth workshop on statistical machine translation, 134-140, 2015 | 161 | 2015 |
| Learning to relate images R Memisevic IEEE transactions on pattern analysis and machine intelligence 35 (8), 1829-1846, 2013 | 129 | 2013 |
| Gated softmax classification R Memisevic, C Zach, M Pollefeys, GE Hinton Advances in neural information processing systems 23, 2010 | 129 | 2010 |
| Learning to solve QBF H Samulowitz, R Memisevic AAAI 7, 255-260, 2007 | 120 | 2007 |
| Modeling deep temporal dependencies with recurrent grammar cells"" V Michalski, R Memisevic, K Konda Advances in neural information processing systems 27, 2014 | 118 | 2014 |
kishore reddy kondaBayesTree Intelligencebayestree.com의 이메일 확인됨
