| Deep complex networks C Trabelsi, O Bilaniuk, Y Zhang, D Serdyuk, S Subramanian, JF Santos, ... arXiv preprint arXiv:1705.09792, 2017 | 1066 | 2017 |
| A meta-transfer objective for learning to disentangle causal mechanisms Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ... arXiv preprint arXiv:1901.10912, 2019 | 399 | 2019 |
| Learning neural causal models from unknown interventions NR Ke, O Bilaniuk, A Goyal, S Bauer, H Larochelle, B Schölkopf, ... arXiv preprint arXiv:1910.01075, 2019 | 186 | 2019 |
| Sparse attentive backtracking: Temporal credit assignment through reminding NR Ke, AG ALIAS PARTH GOYAL, O Bilaniuk, J Binas, MC Mozer, C Pal, ... Advances in neural information processing systems 31, 2018 | 124* | 2018 |
| Learning neural causal models with active interventions N Scherrer, O Bilaniuk, Y Annadani, A Goyal, P Schwab, B Schölkopf, ... arXiv preprint arXiv:2109.02429, 2021 | 43 | 2021 |
| Fast LBP face detection on low-power SIMD architectures O Bilaniuk, E Fazl-Ersi, R Laganiere, C Xu, D Laroche, C Moulder Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 40 | 2014 |
| A fast and robust homography scheme for real-time planar target detection H Bazargani, O Bilaniuk, R Laganiere Journal of Real-Time Image Processing 15 (4), 739-758, 2018 | 28 | 2018 |
| Feedforward initialization for fast inference of deep generative networks is biologically plausible Y Bengio, B Scellier, O Bilaniuk, J Sacramento, W Senn arXiv preprint arXiv:1606.01651, 2016 | 22 | 2016 |
| BARVINN: Arbitrary precision DNN accelerator controlled by a RISC-V CPU M Askarihemmat, S Wagner, O Bilaniuk, Y Hariri, Y Savaria, JP David Proceedings of the 28th Asia and South Pacific Design Automation Conference …, 2023 | 15 | 2023 |
| COVI-AgentSim: an agent-based model for evaluating methods of digital contact tracing P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, A Sharma, ... arXiv preprint arXiv:2010.16004, 2020 | 13 | 2020 |
| Bit-slicing FPGA accelerator for quantized neural networks O Bilaniuk, S Wagner, Y Savaria, JP David 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019 | 13 | 2019 |
| RISC-V barrel processor for deep neural network acceleration MH AskariHemmat, O Bilaniuk, S Wagner, Y Savaria, JP David 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021 | 9 | 2021 |
| Fast target recognition on mobile devices: revisiting gaussian elimination for the estimation of planar homographies O Bilaniuk, H Bazargani, R Laganiere Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 7 | 2014 |
| A meta-transfer objective for learning to disentangle causal mechanisms (2019) Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ... arXiv preprint arXiv:1901.10912, 1901 | 7 | 1901 |
| Neural causal structure discovery from interventions NR Ke, O Bilaniuk, A Goyal, S Bauer, H Larochelle, B Schölkopf, ... Transactions on Machine Learning Research, 2023 | 6 | 2023 |
| Retrieving Signals in the Frequency Domain with Deep Complex Extractors C Trabelsi, O Bilaniuk, O Dia, Y Zhang, M Ravanelli, J Binas, ... | 1* | |
| Introducing Milabench: Benchmarking Accelerators for AI P Delaunay, X Bouthillier, O Breuleux, S Ortiz-Gagné, O Bilaniuk, ... arXiv preprint arXiv:2411.11940, 2024 | | 2024 |
| RISC-V Barrel Processor for Accelerator Control MH AskariHemmat, O Bilaniuk, S Wagner, Y Savaria, JP David 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom …, 2020 | | 2020 |
| Dependency Structure Discovery from Interventions NR Ke, O Bilaniuk, A Goyal, S Bauer, B Schölkopf, MC Mozer, ... | | |
