13 citations · 22 across the 4 of their papers we have counts for
5 papers
Learning to Route: Per-Sample Adaptive Routing for Multimodal Multitask Prediction
Marzieh Ajirak, Oded Bein, Ellen Rose Bowen +5
We propose a unified framework for adaptive routing in multitask, multimodal prediction settings where data heterogeneity and task interactions vary across samples. Motivated by ap…
Uncertainty Quantification in Probabilistic Machine Learning Models: Theory, Methods, and Insights
Marzieh Ajirak, Anand Ravishankar, Petar M. Djuric
Uncertainty Quantification (UQ) is essential in probabilistic machine learning models, particularly for assessing the reliability of predictions. In this paper, we present a system…
Gaussian Process-Gated Hierarchical Mixtures of Experts
Yuhao Liu, Marzieh Ajirak, Petar Djuric
In this paper, we propose novel Gaussian process-gated hierarchical mixtures of experts (GPHMEs). Unlike other mixtures of experts with gating models linear in the input, our model…
Sequential Estimation of Gaussian Process-based Deep State-Space Models
Yuhao Liu, Marzieh Ajirak, Petar Djuric
We consider the problem of sequential estimation of the unknowns of state-space and deep state-space models that include estimation of functions and latent processes of the models.…
Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women
Marzieh Ajirak, Cassandra Heiselman, Anna Fuchs +4
The coronavirus disease (COVID-19) has rapidly spread throughout the world and while pregnant women present the same adverse outcome rates, they are underrepresented in clinical re…