| Learning a Deep ConvNet for Multi-label Classification with Partial Labels T Durand, N Mehrasa, G Mori IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 173 | 2019 |
| A Variational Auto-Encoder Model for Stochastic Point Processes N Mehrasa, A Abdu Jyothi, T Durand, J He, L Sigal, G Mori IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 53 | 2019 |
| Deep learning of player trajectory representations for team activity analysis N Mehrasa, Y Zhong, F Tung, L Bornn, G Mori 11th MIT Sloan Sports Analytics Conference, 2018 | 53* | 2018 |
| Learning Person Trajectory Representations for Team Activity Analysis N Mehrasa, Y Zhong, F Tung, L Bornn, G Mori arXiv preprint arXiv:1706.00893, 2017 | 15 | 2017 |
| Domain Generalization via Semi-supervised Meta Learning H Sharifi-Noghabi, H Asghari, N Mehrasa, M Ester arXiv preprint arXiv:2009.12658, 2020 | 12 | 2020 |
| Point Process Flows N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ... arXiv preprint arXiv:1910.08281, 2019 | 10 | 2019 |
| Systems and Methods for Behaviour Understanding from Trajectories Y ZHONG, N MEHRASA, L BORNN, GP MORI US Patent App. 16/388,588, 2019 | 8 | 2019 |
| System and method for generative model for stochastic point processes N Mehrasa, AA Jyothi, T Durand, J He, M Gregory, M Ahmed, M Brubaker US Patent App. 16/685,327, 2020 | 4 | 2020 |
| Rating and Generating Sudoku Puzzles Based On Constraint Satisfaction Problems B Fatemi, SM Kazemi, N Mehrasa World Academy of Science, Engineering and Technology, International Journal …, 2014 | 4 | 2014 |
| System and method for a convolutional neural network for multi-label classification with partial annotations T Durand, N Mehrasa, M Gregory US Patent App. 16/685,478, 2020 | 3 | 2020 |
| Unsupervised learning of supervoxel embeddings for video Segmentation M Khodabandeh, S Muralidharan, A Vahdat, N Mehrasa, EM Pereira, ... 2016 23rd International Conference on Pattern Recognition (ICPR), 2392-2397, 2016 | 2 | 2016 |
| Towards event analysis in time-series data: Asynchronous probabilistic models and learning from partial labels N Mehrasa Applied Sciences: School of Computing Science, 2021 | | 2021 |
| Arbitrarily-conditioned Data Imputation M Carvalho, T Durand, J He, N Mehrasa, G Mori | | 2019 |
| Learning a Deep ConvNet for Multi-label Classification with Partial Labels-Supplementary T Durand, N Mehrasa, G Mori, B AI | | |
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
