Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning

20 October 2022

Papers citing "Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning"

8 / 8 papers shown

Title
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement Matias Valdenegro-Toro Daniel Saromo UD PER BDL UQCV 56 84 0 20 Apr 2022
Deep Gaussian Processes: A Survey Kalvik Jakkala AI4CE GP BDL 60 21 0 21 Jun 2021
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning A. Tompkins Rafael Oliveira F. Ramos 54 6 0 09 Oct 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 244 1,421 0 21 Oct 2019
Non-Stationary Spectral Kernels Sami Remes Markus Heinonen Samuel Kaski 63 103 0 24 May 2017
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 253 888 0 06 Nov 2015
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo Markus Heinonen Henrik Mannerstrom Juho Rousu Samuel Kaski Harri Lähdesmäki 54 103 0 18 Aug 2015
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression Ville Tolvanen Pasi Jylänki Aki Vehtari 61 61 0 22 Apr 2014