A Variational View on Bootstrap Ensembles as Bayesian Inference

8 June 2020

Papers citing "A Variational View on Bootstrap Ensembles as Bayesian Inference"

10 / 10 papers shown

Title
Bayesian Neural Network Ensembles Tim Pearce Mohamed H. Zaki A. Neely BDL UQCV 50 5 0 27 Nov 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification Dimitrios Milios Raffaello Camoriano Pietro Michiardi Lorenzo Rosasco Maurizio Filippone UQCV 66 75 0 28 May 2018
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 77 276 0 25 Apr 2017
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 78 666 0 27 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 70 1,092 0 16 Aug 2016
A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation Qiang Liu Jason D. Lee Michael I. Jordan 105 485 0 10 Feb 2016
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks Stefan Lee Senthil Purushwalkam Michael Cogswell David J. Crandall Dhruv Batra FedML UQCV 108 315 0 19 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 437 20,568 0 10 Sep 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 106 910 0 17 Feb 2014