| TADAM: Task dependent adaptive metric for improved few-shot learning B Oreshkin, PR López, A Lacoste NeurIPS 2018, 2018 | 356 | 2018 |
| Machine learning approaches to network anomaly detection T Ahmed, B Oreshkin, M Coates Proceedings of the 2nd USENIX workshop on Tackling computer systems problems …, 2007 | 153 | 2007 |
| Optimization and analysis of distributed averaging with short node memory BN Oreshkin, MJ Coates, MG Rabbat IEEE Transactions on Signal Processing 58 (5), 2850-2865, 2010 | 119 | 2010 |
| Accelerated distributed average consensus via localized node state prediction TC Aysal, BN Oreshkin, MJ Coates IEEE Transactions on signal processing 57 (4), 1563-1576, 2008 | 99 | 2008 |
| Asynchronous distributed particle filter via decentralized evaluation of Gaussian products BN Oreshkin, MJ Coates 2010 13th International Conference on Information Fusion, 1-8, 2010 | 64 | 2010 |
| Random numbers for parallel computers: Requirements and methods, with emphasis on GPUs P L’Ecuyer, D Munger, B Oreshkin, R Simard Mathematics and Computers in Simulation 135, 3-17, 2017 | 51* | 2017 |
| Greedy gossip with eavesdropping D Ustebay, BN Oreshkin, MJ Coates, MG Rabbat IEEE Transactions on Signal Processing 58 (7), 3765-3776, 2010 | 51 | 2010 |
| N-BEATS: Neural basis expansion analysis for interpretable time series forecasting BN Oreshkin, D Carpov, N Chapados, Y Bengio ICLR 2020, 2020 | 41 | 2020 |
| AMP: Adaptive masked proxies for few-shot segmentation M Siam, BN Oreshkin, M Jagersand ICCV 2019, 2019 | 37* | 2019 |
| Adaptive cross-modal few-shot learning C Xing, N Rostamzadeh, B Oreshkin, POO Pinheiro NeurIPS 2019, 2019 | 34 | 2019 |
| Rate-based daily arrival process models with application to call centers BN Oreshkin, N Réegnard, P L’Ecuyer Operations Research 64 (2), 510-527, 2016 | 29 | 2016 |
| Microwave radar and microwave-induced thermoacoustics: Dual-modality approach for breast cancer detection E Kirshin, B Oreshkin, GK Zhu, M Popovic, M Coates IEEE Transactions on Biomedical Engineering 60 (2), 354-360, 2012 | 24 | 2012 |
| Deep Prior A Lacoste, T Boquet, N Rostamzadeh, B Oreshkin, W Chung, D Krueger Bayesian Deep Learning @ NIPS 2017, 2017 | 23* | 2017 |
| Efficient delay-tolerant particle filtering BN Oreshkin, X Liu, MJ Coates IEEE Transactions on Signal Processing 59 (7), 3369-3381, 2011 | 21 | 2011 |
| Rates of convergence for greedy gossip with eavesdropping D Ustebay, B Oreshkin, M Coates, M Rabbat 2008 46th Annual Allerton Conference on Communication, Control, and …, 2008 | 18 | 2008 |
| Regional innovation clusters and firm innovation performance: An interactionist approach E Turkina, B Oreshkin, R Kali Regional Studies 53 (8), 1193-1206, 2019 | 16 | 2019 |
| Distributed average consensus with increased convergence rate BN Oreshkin, TC Aysal, MJ Coates 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 15 | 2008 |
| Spatial and probabilistic codebook template based head pose estimation from unconstrained environments M Demirkus, B Oreshkin, JJ Clark, T Arbel 2011 18th IEEE International Conference on Image Processing, 573-576, 2011 | 13 | 2011 |
| Efficient delay-tolerant particle filtering through selective processing of out-of-sequence measurements X Liu, BN Oreshkin, MJ Coates 2010 13th International Conference on Information Fusion, 1-8, 2010 | 11 | 2010 |
| Analysis of error propagation in particle filters with approximation BN Oreshkin, MJ Coates The Annals of Applied Probability 21 (6), 2343-2378, 2011 | 10 | 2011 |
Mark CoatesProfessor of Electrical Engineering, McGill UniversityVerified email at ece.mcgill.ca
