147 citations · 448 across the 18 of their papers we have counts for
4 papers · 1 filter
Statistical Model Aggregation via Parameter Matching
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh +2
We consider the problem of aggregating models learned from sequestered, possibly heterogeneous datasets. Exploiting tools from Bayesian nonparametrics, we develop a general meta-mo…
Quality of Uncertainty Quantification for Bayesian Neural Network Inference
Jiayu Yao, Weiwei Pan, Soumya Ghosh +1
Bayesian Neural Networks (BNNs) place priors over the parameters in a neural network. Inference in BNNs, however, is difficult; all inference methods for BNNs are approximate. In t…
Bayesian Nonparametric Federated Learning of Neural Networks
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh +3
In federated learning problems, data is scattered across different servers and exchanging or pooling it is often impractical or prohibited. We develop a Bayesian nonparametric fram…
DPVis: Visual Analytics with Hidden Markov Models for Disease Progression Pathways
Bum Chul Kwon, Vibha Anand, Kristen A Severson +5
Clinical researchers use disease progression models to understand patient status and characterize progression patterns from longitudinal health records. One approach for disease pr…