3 papers
stat.ML2025
Gaussian Process Assisted Meta-learning for Image Classification and Object Detection Models
Anna R. Flowers, Christopher T. Franck, Robert B. Gramacy +1
Collecting operationally realistic data to inform machine learning models can be costly. Before collecting new data, it is helpful to understand where a model is deficient. For exa…
cs.LG2025
Detecting Urban PM Hotspots with Mobile Sensing and Gaussian Process Regression
Niál Perry, Peter P. Pedersen, Charles N. Christensen +6
Low-cost mobile sensors can be used to collect PM concentration data throughout an entire city. However, identifying air pollution hotspots from the data is challenging due…
stat.ME2025
Modular Jump Gaussian Processes
Anna R. Flowers, Christopher T. Franck, Mickaël Binois +2
Gaussian processes (GPs) furnish accurate nonlinear predictions with well-calibrated uncertainty. However, the typical GP setup has a built-in stationarity assumption, making it il…