SPAHM: Parameter matching for model fusion
Soumya Ghosh
Research Staff Member

Who they work with
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Recent Highlights
- A comprehensive overview of learning Bayesian neural networks with Horseshoe priors will appear in JMLR.
- New code release for distance dependent Chinese restaurant processes. The code by Ishana Shastri is an efficient, python translated, version of this old MATLAB package.
- Our Work on using Bayesian non-parametric meta models for fusing local models will appear at NeurIPS 2019.
- Commonly used metrics such as test log likelihoods can be misleading indicators of posterior quality of BNNs. Preliminary work will appear at Uncertainty and Robustness workshop at ICML’ 19.
Publications with the MIT-IBM Watson AI Lab
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting