528 citations · 4.4k across the 100 of their papers we have counts for
4 papers · 2 filters
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction
William Herlands, Daniel B. Neill, Hannes Nickisch +1
Identifying changes in model parameters is fundamental in machine learning and statistics. However, standard changepoint models are limited in expressiveness, often addressing unid…
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
William Herlands, Edward McFowland, Andrew Gordon Wilson +1
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately cons…
Scalable Lévy Process Priors for Spectral Kernel Learning
Phillip A. Jang, Andrew E. Loeb, Matthew B. Davidow +1
Gaussian processes are rich distributions over functions, with generalization properties determined by a kernel function. When used for long-range extrapolation, predictions are pa…
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin +2
The loss functions of deep neural networks are complex and their geometric properties are not well understood. We show that the optima of these complex loss functions are in fact c…