SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient

11 November 2018

Mohammad Emtiyaz Khan

BDL

UQCV

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Papers citing "SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient"

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Title
Staying Alive: Online Neural Network Maintenance and Systemic Drift Joshua Edward Hammond Tyler Soderstrom Brian A. Korgel Michael Baldea 48 0 0 22 Mar 2025
Low Rank Field-Weighted Factorization Machines for Low Latency Item Recommendation Alicia Y. Tsai Michael Viderman Anahita Hosseini Zemin Zhang Ariel Raviv Lichan Hong 29 0 0 22 Jul 2024
Bayesian Online Natural Gradient (BONG) Matt Jones Peter Chang Kevin P. Murphy BDL 50 4 0 30 May 2024
Favour: FAst Variance Operator for Uncertainty Rating Thomas Dybdahl Ahle Sahar Karimi Peter Tak Peter Tang BDL 29 0 0 21 Nov 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 56 18 0 28 Sep 2023
Low-rank extended Kalman filtering for online learning of neural networks from streaming data Peter Chang Gerardo Duran-Martín Alexander Y. Shestopaloff Matt Jones Kevin P. Murphy BDL 46 17 0 31 May 2023
FineMorphs: Affine-diffeomorphic sequences for regression Michele Lohr L. Younes 31 0 0 26 May 2023
Natural Gradient Hybrid Variational Inference with Application to Deep Mixed Models Weiben Zhang M. Smith Worapree Maneesoonthorn Rubén Loaiza-Maya 16 1 0 27 Feb 2023
A Survey on Uncertainty Quantification Methods for Deep Learning Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Yukun Li BDL UQCV AI4CE 27 19 0 26 Feb 2023
Probabilistic Circuits That Know What They Don't Know Fabrizio G. Ventola Steven Braun Zhongjie Yu Martin Mundt Kristian Kersting UQCV TPM 34 7 0 13 Feb 2023
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 46 7 0 01 Dec 2022
On the detrimental effect of invariances in the likelihood for variational inference Richard Kurle R. Herbrich Tim Januschowski Bernie Wang Jan Gasthaus 35 9 0 15 Sep 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 42 5 0 22 Jun 2022
Amortized Proximal Optimization Juhan Bae Paul Vicol Jeff Z. HaoChen Roger C. Grosse ODL 33 14 0 28 Feb 2022
Implicit copula variational inference M. Smith Rubén Loaiza-Maya 16 7 0 18 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 29 58 0 03 Nov 2021
Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization Dinesh Singh Hardik Tankaria M. Yamada ODL 47 2 0 16 Oct 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 39 9 0 08 Oct 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 68 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 66 1,112 0 07 Jul 2021
Quantum Speedup of Natural Gradient for Variational Bayes A. Lopatnikova Minh-Ngoc Tran BDL 26 3 0 10 Jun 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights H. Ritter Martin Kukla Chen Zhang Yingzhen Li UQCV BDL 63 17 0 30 May 2021
Structured Dropout Variational Inference for Bayesian Neural Networks S. Nguyen Duong Nguyen Khai Nguyen Khoat Than Hung Bui Nhat Ho BDL DRL 8 7 0 16 Feb 2021
Tractable structured natural gradient descent using local parameterizations Wu Lin Frank Nielsen Mohammad Emtiyaz Khan Mark Schmidt 31 29 0 15 Feb 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch BDL UQCV 22 22 0 04 Dec 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 56 1,883 0 12 Nov 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 31 84 0 28 Oct 2020
Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks Alexander Immer BDL 19 4 0 21 Jul 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 38 46 0 20 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 19 38 0 18 Jun 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 31 45 0 07 Feb 2020
Kernelized Wasserstein Natural Gradient Michael Arbel Arthur Gretton Wuchen Li Guido Montúfar 26 22 0 21 Oct 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation Konstantinos Pitas 19 8 0 06 Sep 2019
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 14 38 0 09 Aug 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations Wu Lin Mohammad Emtiyaz Khan Mark Schmidt BDL 11 69 0 07 Jun 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent Frederik Kunstner Lukas Balles Philipp Hennig 23 209 0 29 May 2019
Copula-like Variational Inference Marcel Hirt P. Dellaportas Alain Durmus 12 5 0 15 Apr 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 19 6 0 11 Feb 2019
Eigenvalue Corrected Noisy Natural Gradient Juhan Bae Guodong Zhang Roger C. Grosse 28 16 0 30 Nov 2018
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 74 268 0 13 Jun 2018
Lifelong Generative Modeling Jason Ramapuram Magda Gregorova Alexandros Kalousis BDL CLL 24 119 0 27 May 2017
Efficient Per-Example Gradient Computations Ian Goodfellow 186 75 0 07 Oct 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015