
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI
In this paper, we describe an open source Python toolkit named Uncertain...
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Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals
Accurate quantification of model uncertainty has long been recognized as...
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EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders
Researchers require timely access to realworld longitudinal electronic ...
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Model Fusion with Kullback–Leibler Divergence
We propose a method to fuse posterior distributions learned from heterog...
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Mobility driven CloudFogEdge Framework for Locationaware Services: A Comprehensive Review
With the pervasiveness of IoT devices, smartphones and improvement of l...
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Approximate CrossValidation for Structured Models
Many modern data analyses benefit from explicitly modeling dependence st...
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Statistical Model Aggregation via Parameter Matching
We consider the problem of aggregating models learned from sequestered, ...
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Quality of Uncertainty Quantification for Bayesian Neural Network Inference
Bayesian Neural Networks (BNNs) place priors over the parameters in a ne...
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Bayesian Nonparametric Federated Learning of Neural Networks
In federated learning problems, data is scattered across different serve...
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DPVis: Visual Exploration of Disease Progression Pathways
Clinical researchers use disease progression modeling algorithms to pred...
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Latent Projection BNNs: Avoiding weightspace pathologies by learning latent representations of neural network weights
While modern neural networks are making remarkable gains in terms of pre...
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Unsupervised learning with contrastive latent variable models
In unsupervised learning, dimensionality reduction is an important tool ...
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Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Bayesian Neural Networks (BNNs) have recently received increasing attent...
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Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care
Type 2 diabetes mellitus (T2DM) is a chronic disease that often results ...
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Model Selection in Bayesian Neural Networks via Horseshoe Priors
Bayesian Neural Networks (BNNs) have recently received increasing attent...
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Soumya Ghosh
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