| Patient subtyping via time-aware LSTM networks IM Baytas, C Xiao, X Zhang, F Wang, AK Jain, J Zhou Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 747 | 2017 |
| Privacy-preserving distributed multi-task learning with asynchronous updates L Xie, IM Baytas, K Lin, J Zhou Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 59 | 2017 |
| Asynchronous multi-task learning IM Baytas, M Yan, AK Jain, J Zhou 2016 IEEE 16th International Conference on Data Mining (ICDM), 11-20, 2016 | 56 | 2016 |
| Heterogeneous hyper-network embedding IM Baytas, C Xiao, F Wang, AK Jain, J Zhou 2018 IEEE International Conference on Data Mining (ICDM), 875-880, 2018 | 38 | 2018 |
| Multi-task feature interaction learning K Lin, J Xu, IM Baytas, S Ji, J Zhou Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge …, 2016 | 38 | 2016 |
| An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence C Xiao, Y Li, I Baytas, J Zhou, F Wang Scientific Reports 8, 2018 | 29 | 2018 |
| PhenoTree: interactive visual analytics for hierarchical phenotyping from large-scale electronic health records IM Baytas, K Lin, F Wang, AK Jain, J Zhou IEEE Transactions on Multimedia 18 (11), 2257-2270, 2016 | 24 | 2016 |
| Subspace network: Deep multi-task censored regression for modeling neurodegenerative diseases M Sun, IM Baytas, L Zhan, Z Wang, J Zhou Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 15 | 2018 |
| Multi-cue temporal modeling for skeleton-based sign language recognition O Özdemir, İM Baytaş, L Akarun Frontiers in Neuroscience 17, 1148191, 2023 | 10 | 2023 |
| Robustness-via-synthesis: Robust training with generative adversarial perturbations İM Baytaş, D Deb Neurocomputing 516, 49-60, 2023 | 9 | 2023 |
| Investigating conversion from mild cognitive impairment to alzheimer’s disease using latent space manipulation DS Ayvaz, İM Baytaş The International Symposium on Health Informatics and Bioinformatics, https …, 2022 | 6 | 2022 |
| Stochastic convex sparse principal component analysis IM Baytas, K Lin, F Wang, AK Jain, J Zhou EURASIP Journal on Bioinformatics and Systems Biology 2016, 1-11, 2016 | 6 | 2016 |
| Similarity learning via adaptive regression and its application to image retrieval Q Qian, IM Baytas, R Jin, A Jain, S Zhu arXiv preprint arXiv:1512.01728, 2015 | 3 | 2015 |
| Image Classification on Accelerated Neural Networks I Sikdokur, I Baytas, A Yurdakul arXiv preprint arXiv:2203.11081, 2022 | 2 | 2022 |
| Contributions to Machine Learning in Biomedical Informatics IM Baytas Michigan State University, 2019 | 2 | 2019 |
| Predicting Progression From Mild Cognitive Impairment to Alzheimer's Dementia With Adversarial Attacks İM Baytaş IEEE Journal of Biomedical and Health Informatics, 2024 | 1 | 2024 |
| Adversarial training with orthogonal regularization OK Yüksel, İM Baytaş 2020 28th Signal Processing and Communications Applications Conference (SIU …, 2020 | 1 | 2020 |
| Head motion classification with 2D motion estimation İM Baytaş, B Günsel 2014 22nd Signal Processing and Communications Applications Conference (SIU …, 2014 | 1 | 2014 |
| Adversarial Robustness for Deep Metric Learning E Paket, İM Baytaş 2024 IEEE International Conference on Image Processing (ICIP), 367-373, 2024 | | 2024 |
| EdgeConvEns: Convolutional Ensemble Learning for Edge Intelligence I Sikdokur, İM Baytaş, A Yurdakul IEEE Access, 2024 | | 2024 |
Jiayu ZhouUniversity of MichiganDirección de correo verificada de umich.edu
