Deep Gaussian Processes: A Survey

21 June 2021

Papers citing "Deep Gaussian Processes: A Survey"

12 / 12 papers shown

Title
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes Jie Liu Pan Zhou Zehao Xiao Jiayi Shen Wenzhe Yin J. Sonke E. Gavves 31 0 0 03 May 2025
Distributed Coverage Control for Time-Varying Spatial Processes Federico Pratissoli Mattia Mantovani Amanda Prorok Lorenzo Sabattini 59 0 0 11 Feb 2025
Knowledge-aware Evolutionary Graph Neural Architecture Search Chao Wang Jiaxuan Zhao Lingling Li Licheng Jiao Fang Liu Xu Liu S. M. I. Simon X. Yang 80 2 0 26 Nov 2024
Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 65 1 0 21 May 2024
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 21 9 0 20 Jun 2023
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 35 68 0 21 Nov 2022
Deep Gaussian Processes for Air Quality Inference Aadesh Desai Eshan Gujarathi Saagar Parikh Sachin Yadav Zeel B Patel Nipun Batra 31 2 0 18 Nov 2022
Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning Zeel B Patel Nipun Batra Kevin P. Murphy UD PER UQCV 29 1 0 20 Oct 2022
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization S. Petit Julien Bect E. Vázquez 33 1 0 07 Jun 2022
Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning René Zurbrugg Hermann Blum César Cadena Roland Siegwart L. Schmid SSeg 33 21 0 01 Mar 2022
Multi-Task Neural Processes Jiayi Shen Xiantong Zhen M. Worring Ling Shao BDL 16 8 0 10 Nov 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015