Deep learning for patient-specific kidney graft survival analysis M Luck*, T Sylvain*, H Cardinal, A Lodi, Y Bengio arXiv preprint arXiv:1705.10245, 2017 | 143 | 2017 |
Object-centric image generation from layouts T Sylvain, P Zhang, Y Bengio, RD Hjelm, S Sharma AAAI 2021, arXiv preprint arXiv:2003.07449, 2020 | 103 | 2020 |
Diet networks: thin parameters for fat genomics A Romero, PL Carrier, A Erraqabi, T Sylvain, A Auvolat, E Dejoie, ... ICLR 2017, arXiv preprint arXiv:1611.09340, 2016 | 83 | 2016 |
Scaleformer: iterative multi-scale refining transformers for time series forecasting A Shabani, A Abdi, L Meng, T Sylvain ICLR 2023, 2023 | 66 | 2023 |
Locality and compositionality in zero-shot learning T Sylvain, L Petrini, D Hjelm ICLR 2020, arXiv preprint arXiv:1912.12179, 2019 | 61 | 2019 |
On self-supervised multimodal representation learning: an application to Alzheimer’s disease A Fedorov, L Wu, T Sylvain, M Luck, TP DeRamus, D Bleklov, SM Plis, ... 2021 IEEE 18th international symposium on biomedical imaging (ISBI), 1548-1552, 2021 | 23 | 2021 |
Self-supervised multimodal domino: in search of biomarkers for alzheimer’s disease A Fedorov, T Sylvain, E Geenjaar, M Luck, L Wu, TP DeRamus, A Kirilin, ... 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), 23-30, 2021 | 13* | 2021 |
CMIM: Cross-Modal Information Maximization For Medical Imaging T Sylvain, F Dutil, T Berthier, L Di Jorio, M Luck, D Hjelm, Y Bengio ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 11* | 2021 |
Zero-Shot Learning from scratch: leveraging local compositional representations T Sylvain, L Petrini, D Hjelm (spotlight) ICML 2019 Workshop on Understanding and Improving Generalization …, 2019 | 9 | 2019 |
Deep learning for patient-specific kidney graft survival analysis. arXiv 2017 M Luck, T Sylvain, H Cardinal, A Lodi, Y Bengio arXiv preprint arXiv:1705.10245, 2020 | 6 | 2020 |
Deep learning for patient-specific kidney graft survival analysis. arXiv M Luck, T Sylvain, H Cardinal, A Lodi, Y Bengio arXiv preprint arXiv:1705.10245, 2017 | 6 | 2017 |
Joint Learning of Generative Translator and Classifier for Visually Similar Classes BI Yoo, T Sylvain, Y Bengio, J Kim IEEE Access, 2019 | 5 | 2019 |
Learning to rank for censored survival data M Luck, T Sylvain, JP Cohen, H Cardinal, A Lodi, Y Bengio ICML 2018 Workshop in Computational Biology, arXiv preprint arXiv:1806.01984, 2018 | 4 | 2018 |
Autocast++: Enhancing world event prediction with zero-shot ranking-based context retrieval Q Yan, R Seraj, J He, L Meng, T Sylvain ICLR 2024, arXiv preprint arXiv:2310.01880, 2023 | 3 | 2023 |
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links A Fedorov, E Geenjaar, L Wu, T Sylvain, TP DeRamus, M Luck, M Misiura, ... NeuroImage 285, 120485, 2024 | 2 | 2024 |
Robust Reinforcement Learning Objectives for Sequential Recommender Systems M Mozifian, T Sylvain, D Evans, L Meng arXiv preprint arXiv:2305.18820, 2023 | 2 | 2023 |
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes A Fedorov, E Geenjaar, L Wu, T Sylvain, TP DeRamus, M Luck, M Misiura, ... arXiv preprint arXiv:2209.02876, 2022 | 2 | 2022 |
Exploring the wasserstein metric for time-to-event analysis T Sylvain, M Luck, J Cohen, H Cardinal, A Lodi, Y Bengio Survival Prediction-Algorithms, Challenges and Applications, 194-206, 2021 | 2 | 2021 |
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer M Amodio, R Assouel, V Schmidt, T Sylvain, S Krishnaswamy, Y Bengio arXiv preprint arXiv:2006.13291, 2020 | 1 | 2020 |
System and method for a machine learning architecture for resource allocation L Meng, TJC Sylvain, AH Abdi, G Oliveira, Y Rakhmangulova, ... US Patent App. 18/238,397, 2024 | | 2024 |