Approximate Inference Turns Deep Networks into Gaussian Processes

5 June 2019

Mohammad Emtiyaz Khan

Papers citing "Approximate Inference Turns Deep Networks into Gaussian Processes"

35 / 85 papers shown

Title
Deep Ensemble as a Gaussian Process Approximate Posterior Zhijie Deng Feng Zhou Jianfei Chen Guoqiang Wu Jun Zhu UQCV 16 5 0 30 Apr 2022
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 23 34 0 17 Mar 2022
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel Chi-Ken Lu Patrick Shafto BDL 34 0 0 14 Mar 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 24 10 0 28 Feb 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer Tycho F. A. van der Ouderaa Gunnar Rätsch Vincent Fortuin Mark van der Wilk BDL 36 44 0 22 Feb 2022
Stochastic Neural Networks with Infinite Width are Deterministic Liu Ziyin Hanlin Zhang Xiangming Meng Yuting Lu Eric P. Xing Masakuni Ueda 29 3 0 30 Jan 2022
Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning Runa Eschenhagen Erik A. Daxberger Philipp Hennig Agustinus Kristiadi UQCV BDL 30 22 0 05 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 21 15 0 02 Nov 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseo Lee Jianxiang Feng Matthias Humt M. Müller Rudolph Triebel UQCV 48 21 0 20 Sep 2021
Shift-Curvature, SGD, and Generalization Arwen V. Bradley C. Gomez-Uribe Manish Reddy Vuyyuru 32 2 0 21 Aug 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 60 73 0 09 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 35 1,109 0 07 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 49 288 0 28 Jun 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights H. Ritter Martin Kukla Chen Zhang Yingzhen Li UQCV BDL 47 17 0 30 May 2021
Can we imitate the principal investor's behavior to learn option price? Xin Jin 31 0 0 24 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Alexander Immer Matthias Bauer Vincent Fortuin Gunnar Rätsch Mohammad Emtiyaz Khan BDL UQCV 27 102 0 11 Apr 2021
Fast Adaptation with Linearized Neural Networks Wesley J. Maddox Shuai Tang Pablo G. Moreno A. Wilson Andreas C. Damianou 29 32 0 02 Mar 2021
All You Need is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran Simone Rossi Dimitrios Milios Maurizio Filippone OOD BDL 25 56 0 25 Nov 2020
Sample-efficient reinforcement learning using deep Gaussian processes Charles W. L. Gadd Markus Heinonen Harri Lähdesmäki Samuel Kaski GP BDL 15 4 0 02 Nov 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 25 83 0 28 Oct 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 42 24 0 27 Oct 2020
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks Takuo Matsubara Chris J. Oates F. Briol BDL UQCV 13 17 0 16 Oct 2020
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence Agustinus Kristiadi Matthias Hein Philipp Hennig BDL 18 9 0 06 Oct 2020
Improving predictions of Bayesian neural nets via local linearization Alexander Immer M. Korzepa Matthias Bauer BDL 8 11 0 19 Aug 2020
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 6 56 0 14 Aug 2020
Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks Alexander Immer BDL 8 4 0 21 Jul 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 9 116 0 11 Jul 2020
Maximum Multiscale Entropy and Neural Network Regularization Amir-Reza Asadi Emmanuel Abbe 13 1 0 25 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 14 436 0 17 Jun 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
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 14 52 0 21 Apr 2020
Scalable Uncertainty for Computer Vision with Functional Variational Inference Eduardo D C Carvalho R. Clark Andrea Nicastro Paul H. J. Kelly BDL UQCV 131 22 0 06 Mar 2020
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 68 171 0 08 Jul 2017