5 papers
On Counterfactual Interventions in Vector Autoregressive Models
Kurt Butler, Marija Iloska, Petar M. Djuric
Counterfactual reasoning allows us to explore hypothetical scenarios in order to explain the impacts of our decisions. However, addressing such inquires is impossible without estab…
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.…
Explainable Learning with Gaussian Processes
Kurt Butler, Guanchao Feng, Petar M. Djuric
The field of explainable artificial intelligence (XAI) attempts to develop methods that provide insight into how complicated machine learning methods make predictions. Many methods…
Fusion of Gaussian Processes Predictions with Monte Carlo Sampling
Marzieh Ajirak, Daniel Waxman, Fernando Llorente +1
In science and engineering, we often work with models designed for accurate prediction of variables of interest. Recognizing that these models are approximations of reality, it bec…
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…