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.
SupplementPoster
  Spatial distance dependent Chinese restaurant processes for image segmentation
Soumya Ghosh, Andrei Ungureanu, Erik Sudderth, and David Blei
NIPS 2011.
Poster

Dissertation