Practical Deep Learning with Bayesian Principles

6 June 2019

Mohammad Emtiyaz Khan

BDL

UQCV

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Papers citing "Practical Deep Learning with Bayesian Principles"

24 / 174 papers shown

Title
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 31 207 0 14 May 2020
Continual Deep Learning by Functional Regularisation of Memorable Past Pingbo Pan S. Swaroop Alexander Immer Runa Eschenhagen Richard Turner Mohammad Emtiyaz Khan KELM CLL 6 139 0 29 Apr 2020
Practical calibration of the temperature parameter in Gibbs posteriors Lucie Perrotta 6 3 0 22 Apr 2020
Tractable Approximate Gaussian Inference for Bayesian Neural Networks J. Goulet L. Nguyen Saeid Amiri BDL 6 18 0 20 Apr 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Training Binary Neural Networks using the Bayesian Learning Rule Xiangming Meng Roman Bachmann Mohammad Emtiyaz Khan BDL MQ 30 40 0 25 Feb 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule Wu Lin Mark W. Schmidt Mohammad Emtiyaz Khan BDL 37 35 0 24 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
Scalable and Practical Natural Gradient for Large-Scale Deep Learning Kazuki Osawa Yohei Tsuji Yuichiro Ueno Akira Naruse Chuan-Sheng Foo Rio Yokota 31 36 0 13 Feb 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks J. Swiatkowski Kevin Roth Bastiaan S. Veeling Linh-Tam Tran Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Rodolphe Jenatton Sebastian Nowozin BDL 23 45 0 07 Feb 2020
Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning Shi-Ju Ran 8 6 0 30 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection Erik A. Daxberger José Miguel Hernández-Lobato UQCV 18 63 0 11 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 8 23 0 04 Dec 2019
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure Zhijie Deng Yucen Luo Jun Zhu Bo Zhang UQCV BDL 19 2 0 22 Nov 2019
Entropy from Machine Learning R. Janik 14 5 0 24 Sep 2019
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 6 38 0 09 Aug 2019
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning Sebastian Farquhar Michael A. Osborne Y. Gal UQCV BDL 21 57 0 01 Jul 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 25 122 0 05 Jun 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 16 32 0 15 Feb 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 65 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Efficient Per-Example Gradient Computations Ian Goodfellow 186 74 0 07 Oct 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015