Selected Publications


For a complete list see my Google Scholar profile.	Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre Dognin and Kush R. Varshney NeurIPS 2022.
	Measuring the robustness of Gaussian processes to kernel choice William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Sameer K. Deshpande and Tamara Broderick AISTATS 2022.	Code
	Approximate Cross-Validation for Structured Models Soumya Ghosh⁺, William T. Stephenson⁺, Tin D. Nguyen, Sameer K. Deshpande and Tamara Broderick NeurIPS 2020. + Equal contributions	Code
	Model Selection in Bayesian Neural Networks via Horseshoe Priors Soumya Ghosh, Jiayu Yao, and Finale Doshi-Velez Journal of Machine Learning Research, 2019. Summarizes and distills insights from our previous conference papers on this topic.	Code
	Statistical Model Aggregation via Parameter Matching Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald and Nghia Hoang NeurIPS 2019.	Supplement Code Poster
	Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang and Yasaman Khazaeni ICML 2019.	Supplement Code
	Unsupervised Learning with Contrastive Latent Variable Models Kristen Severson, Soumya Ghosh and Kenney Ng AAAI 2019.	Code Slides
	Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors Soumya Ghosh, Jiayu Yao, and Finale Doshi-Velez ICML 2018.	Code Poster Slides
	Early Prediction of Diabetes Complications from Electronic Health Records: A Multi-task Survival Analysis Approach Bin Liu, Ying Li, Zhaonan Sun, Soumya Ghosh, and Kenney Ng AAAI 2018.	Slides
	Model Selection in Bayesian Neural Networks via Horseshoe Priors Soumya Ghosh and Finale Doshi-Velez NIPS 2017, Workshop on Bayesian Deep Learning ArXiv version	Code Poster Slides
	Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks Ajjen Joshi, Soumya Ghosh, Margrit Betke, Stan Scarloff, and Hanspeter Pfister CVPR 2017. Hierarchical Bayesian Neural Networks for Personalized Classification Ajjen Joshi, Soumya Ghosh, Margrit Betke, and Hanspeter Pfister NIPS 2016. Workshop on Bayesian Deep Learning.	Supplement Poster Spotlight
	An Exploration of Latent Structure in Observational Huntington’s Disease Studies Soumya Ghosh, Zhaonan Sun, Ying Li, Yu Cheng, Amrita Mohan, Cristina Sampaio, and Jianying Hu AMIA CRI 2017.	Slides
	Assumed Density Filtering Methods for Learning Bayesian Neural Networks Soumya Ghosh, Francesco DelleFave, and Jonathan Yedidia AAAI 2016.	Slides
	Approximate Bayesian Computation for Distance-Dependent Learning Soumya Ghosh and Erik Sudderth NIPS 2015. Workshop on Bayesian Nonparametrics: The Next Generation.
	Nonparametric Clustering with Distance Dependent Hierarchies Soumya Ghosh, Michalis Raptis, Leonid Sigal, and Erik Sudderth UAI 2014.	Supplement Spotlight
	From Deformations to Parts:Motion-based Segmentation of 3D Objects Soumya Ghosh, Erik Sudderth, Mathew Loper, and Michael Black NIPS 2012.	Supplement Code
	Nonparametric Learning for Layered Segmentation of Natural Images Soumya Ghosh and Erik Sudderth CVPR 2012.	Supplement Poster
	Spatial distance dependent Chinese restaurant processes for image segmentation Soumya Ghosh, Andrei Ungureanu, Erik Sudderth, and David Blei NIPS 2011.	Poster

Dissertation

Bayesian nonparametric discovery of layers and parts from scenes and objects
Soumya Ghosh, Brown University, 2015.
Slides