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Soumya Ghosh

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Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions

Feb 09, 2024
J. Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell

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Assessment of Prediction Intervals Using Uncertainty Characteristics Curves

Oct 04, 2023
Jiri Navratil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri

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Reliable Gradient-free and Likelihood-free Prompt Tuning

Apr 30, 2023
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory Wornell

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Post-hoc Uncertainty Learning using a Dirichlet Meta-Model

Dec 14, 2022
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory Wornell

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Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting

Dec 13, 2022
Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre Dognin, Kush R. Varshney

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Are you using test log-likelihood correctly?

Dec 01, 2022
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick

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Post-hoc loss-calibration for Bayesian neural networks

Jun 13, 2021
Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin

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Measuring the sensitivity of Gaussian processes to kernel choice

Jun 11, 2021
William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick

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Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI

Jun 04, 2021
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jiri Navratil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

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