2 papers
stat.ML2026
Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs
Nathan Weill, Kaizheng Wang
We propose a principled framework for unsupervised domain adaptation under covariate shift in kernel Generalized Linear Models (GLMs), encompassing kernelized linear, logistic, and…
cs.LG2023
Deep Generative Methods for Producing Forecast Trajectories in Power Systems
Nathan Weill, Jonathan Dumas
With the expansion of renewables in the electricity mix, power grid variability will increase, hence a need to robustify the system to guarantee its security. Therefore, Transport…