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09/06/2023
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks
Bayesian inference for neural networks, or Bayesian deep learning, has t...
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08/17/2023
A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks
Network complexity and computational efficiency have become increasingly...
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06/14/2023
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
Modern climate projections lack adequate spatial and temporal resolution...
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10/08/2022
Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness
Robust machine learning models with accurately calibrated uncertainties ...
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06/01/2022
Sequential Bayesian Neural Subnetwork Ensembles
Deep neural network ensembles that appeal to model diversity have been u...
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04/05/2022
Bayesian Quantile Regression for Longitudinal Count Data
This work introduces Bayesian quantile regression modeling framework for...
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08/25/2021
