Introduction to General and Generalized Linear Models

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Less is More: Culling the Training Set to Improve Robustness of Deep Neural Networks (2018, background): “Influence Sketching [19] proposed a new scalable version of Cooks distance [3, 4] to prioritize samples in the generalized linear model [12].”
Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction (2015, methodology): “The idea was to infer spike times as a Bayesian inverse problem and then estimate the Generalized Linear Model (GLM) [9] kernels which were a measure of connectome weights of neurons.”
Foundations of Linear and Generalized Linear Models (2015, methodology): “Broader overviews of generalized linear modeling include the classic book by McCullagh and Nelder (1989) and the more recent book by Aitkin et al.”
Identifying suitable models for the heat dynamics of buildings (2011, unknown): “[10].”