Self-explaining variational posterior distributions for Gaussian Process models

8 September 2021

Papers citing "Self-explaining variational posterior distributions for Gaussian Process models"

6 / 6 papers shown

Title
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior Rajarshi Guhaniyogi Cheng Li T. Savitsky Sanvesh Srivastava 30 20 0 01 Jun 2020
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 69 106 0 03 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 53 638 0 29 Mar 2019
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 118 940 0 20 Jun 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 276 2,257 0 24 Jun 2017
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 98 1,230 0 26 Sep 2013