| Bayesian nonparametric federated learning of neural networks M Yurochkin, M Agarwal, S Ghosh, K Greenewald, N Hoang, Y Khazaeni International conference on machine learning, 7252-7261, 2019 | 618 | 2019 |
| Model Selection in Bayesian Neural Networks via Horseshoe Priors. S Ghosh, J Yao, F Doshi-Velez J. Mach. Learn. Res. 20 (182), 1-46, 2019 | 138 | 2019 |
| Quality of uncertainty quantification for Bayesian neural network inference J Yao, W Pan, S Ghosh, F Doshi-Velez arXiv preprint arXiv:1906.09686, 2019 | 119 | 2019 |
| Spatial distance dependent Chinese restaurant processes for image segmentation S Ghosh, A Ungureanu, E Sudderth, D Blei Advances in Neural Information Processing Systems 24, 2011 | 100 | 2011 |
| Structured variational learning of Bayesian neural networks with horseshoe priors S Ghosh, J Yao, F Doshi-Velez International Conference on Machine Learning, 1744-1753, 2018 | 84 | 2018 |
| DPVis: Visual analytics with hidden markov models for disease progression pathways BC Kwon, V Anand, KA Severson, S Ghosh, Z Sun, BI Frohnert, ... IEEE transactions on visualization and computer graphics 27 (9), 3685-3700, 2020 | 62 | 2020 |
| Assumed density filtering methods for learning bayesian neural networks S Ghosh, F Delle Fave, J Yedidia Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 59 | 2016 |
| Automatic recognition of landforms on Mars using terrain segmentation and classification TF Stepinski, S Ghosh, R Vilalta International Conference on Discovery Science, 255-266, 2006 | 45 | 2006 |
| Early prediction of diabetes complications from electronic health records: A multi-task survival analysis approach B Liu, Y Li, Z Sun, S Ghosh, K Ng Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 43 | 2018 |
| Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning KA Severson, LM Chahine, LA Smolensky, M Dhuliawala, M Frasier, K Ng, ... The Lancet Digital Health 3 (9), e555-e564, 2021 | 42 | 2021 |
| A probabilistic disease progression modeling approach and its application to integrated Huntington’s disease observational data Z Sun, S Ghosh, Y Li, Y Cheng, A Mohan, C Sampaio, J Hu JAMIA open 2 (1), 123-130, 2019 | 40 | 2019 |
| Unsupervised learning with contrastive latent variable models KA Severson, S Ghosh, K Ng Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4862-4869, 2019 | 39 | 2019 |
| Automatic annotation of planetary surfaces with geomorphic labels S Ghosh, TF Stepinski, R Vilalta IEEE Transactions on Geoscience and Remote Sensing 48 (1), 175-185, 2009 | 35 | 2009 |
| Statistical model aggregation via parameter matching M Yurochkin, M Agarwal, S Ghosh, K Greenewald, N Hoang Advances in neural information processing systems 32, 2019 | 34 | 2019 |
| Personalizing gesture recognition using hierarchical bayesian neural networks A Joshi, S Ghosh, M Betke, S Sclaroff, H Pfister Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 33 | 2017 |
| Model fusion with Kullback-Leibler divergence S Claici, M Yurochkin, S Ghosh, J Solomon International conference on machine learning, 2038-2047, 2020 | 31 | 2020 |
| Personalized input-output hidden markov models for disease progression modeling KA Severson, LM Chahine, L Smolensky, K Ng, J Hu, S Ghosh Machine learning for healthcare conference, 309-330, 2020 | 30 | 2020 |
| EVA: Generating longitudinal electronic health records using conditional variational autoencoders S Biswal, S Ghosh, J Duke, B Malin, W Stewart, C Xiao, J Sun Machine Learning for Healthcare Conference, 260-282, 2021 | 29 | 2021 |
| Uncertainty quantification 360: A holistic toolkit for quantifying and communicating the uncertainty of ai S Ghosh, QV Liao, KN Ramamurthy, J Navratil, P Sattigeri, KR Varshney, ... arXiv preprint arXiv:2106.01410, 2021 | 28 | 2021 |
| Machine learning for automatic mapping of planetary surfaces TF Stepinski, S Ghosh, R Vilalta Proceedings of the National Conference on Artificial Intelligence 22 (2), 1807, 2007 | 27 | 2007 |
Mikhail YurochkinResearch Staff Member, IBM Research and MIT-IBM Watson AI LabDirección de correo verificada de umich.edu
