| Motion In-Betweening via Deep -Interpolator BN Oreshkin, A Valkanas, FG Harvey, LS Ménard, F Bocquelet, ... IEEE Transactions on Visualization and Computer Graphics, 2023 | 17 | 2023 |
| Bag Graph: Multiple Instance Learning using Bayesian Graph Neural Networks S Pal, A Valkanas, F Regol, M Coates Proceedings of the AAAI Conference on Artificial Intelligence 36 7, 7922-7930, 2022 | 14 | 2022 |
| Surfing the radio spectrum using RTL-SDR A Valkanas, D Pandey, H Leib IETE Journal of Education 60 (2), 65-73, 2019 | 4 | 2019 |
| Structure aware incremental learning with personalized imitation weights for recommender systems Y Wang, Y Zhang, A Valkanas, R Tang, C Ma, J Hao, M Coates Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4711-4719, 2023 | 2 | 2023 |
| Learning from networks of distributions A Valkanas, F Regol, M Coates 2020 54th Asilomar Conference on Signals, Systems, and Computers, 574-578, 2020 | 2 | 2020 |
| A neural network based electromagnetic simulator A Valkanas, D Giannacopoulos 2019 22nd International Conference on the Computation of Electromagnetic …, 2019 | 2 | 2019 |
| Personalized Negative Reservoir for Incremental Learning in Recommender Systems A Valkanas, Y Wang, Y Zhang, M Coates arXiv preprint arXiv:2403.03993, 2024 | | 2024 |
| Population Monte Carlo with Normalizing Flow S Pal, A Valkanas, M Coates IEEE Signal Processing Letters, 2023 | | 2023 |
| Towards Bayesian Learning of the Architecture, Graph and Parameters for Graph Neural Networks A Valkanas, AW Panzini, M Coates 2022 56th Asilomar Conference on Signals, Systems, and Computers, 852-856, 2022 | | 2022 |
| Contrastive Learning for Time Series on Dynamic Graphs Y Zhang, F Regol, A Valkanas, M Coates 2022 30th European Signal Processing Conference (EUSIPCO), 742-746, 2022 | | 2022 |
| Graph modelling of bag relations in multiple instance learning A Valkanas McGill University (Canada), 2021 | | 2021 |
Mark CoatesProfessor of Electrical Engineering, McGill UniversityVerified email at ece.mcgill.ca
