Soumya Ghosh
Soumya Ghosh
MIT-IBM Watson AI Lab, IBM Research
Geverifieerd e-mailadres voor cs.brown.edu - Homepage
Geciteerd door
Geciteerd door
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
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
Quality of uncertainty quantification for Bayesian neural network inference
J Yao, W Pan, S Ghosh, F Doshi-Velez
arXiv preprint arXiv:1906.09686, 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
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
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
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
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
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
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
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
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
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
Statistical model aggregation via parameter matching
M Yurochkin, M Agarwal, S Ghosh, K Greenewald, N Hoang
Advances in neural information processing systems 32, 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
Model fusion with Kullback-Leibler divergence
S Claici, M Yurochkin, S Ghosh, J Solomon
International conference on machine learning, 2038-2047, 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
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
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
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
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