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"

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Title
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 57 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 32 1,109 0 07 Jul 2021
Probabilistic partition of unity networks: clustering based deep approximation N. Trask Mamikon A. Gulian Andrew Huang Kookjin Lee 11 6 0 07 Jul 2021
Unsupervised Knowledge-Transfer for Learned Image Reconstruction Riccardo Barbano Ž. Kereta A. Hauptmann Simon Arridge Bangti Jin 18 11 0 06 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 43 288 0 28 Jun 2021
Analytically Tractable Bayesian Deep Q-Learning Luong Ha L. Nguyen J. Goulet BDL OffRL 20 2 0 21 Jun 2021
NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights Kirill Bykov Anna Hedström Shinichi Nakajima Marina M.-C. Höhne FAtt 17 34 0 18 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 20 15 0 18 Jun 2021
Natural continual learning: success is a journey, not (just) a destination Ta-Chu Kao Kristopher T. Jensen Gido M. van de Ven A. Bernacchia Guillaume Hennequin CLL 23 46 0 15 Jun 2021
Model Selection for Bayesian Autoencoders Ba-Hien Tran Simone Rossi Dimitrios Milios Pietro Michiardi Edwin V. Bonilla Maurizio Filippone BDL 15 12 0 11 Jun 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 26 37 0 10 Jun 2021
Estimating the Uncertainty of Neural Network Forecasts for Influenza Prevalence Using Web Search Activity Michael Morris Peter A. Hayes Ingemar J. Cox Vasileios Lampos 13 1 0 26 May 2021
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning Yue Wu Shuangfei Zhai Nitish Srivastava J. Susskind Jian Zhang Ruslan Salakhutdinov Hanlin Goh EDL OffRL OnRL 13 183 0 17 May 2021
An Effective Baseline for Robustness to Distributional Shift S. Thulasidasan Sushil Thapa S. Dhaubhadel Gopinath Chennupati Tanmoy Bhattacharya J. Bilmes OOD OODD 26 26 0 15 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions Bertrand Charpentier Oliver Borchert Daniel Zügner Simon Geisler Stephan Günnemann UQCV BDL 22 17 0 10 May 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 17 366 0 29 Apr 2021
Bayesian Deep Neural Networks for Supervised Learning of Single-View Depth Javier Rodríguez-Puigvert Ruben Martinez Cantin Javier Civera UQCV BDL SSL 10 7 0 29 Apr 2021
Scalable Bayesian Deep Learning with Kernel Seed Networks Sam Maksoud Kun-li Zhao Can Peng Brian C. Lovell BDL 14 1 0 19 Apr 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning Alexander Immer Matthias Bauer Vincent Fortuin Gunnar Rätsch Mohammad Emtiyaz Khan BDL UQCV 25 102 0 11 Apr 2021
Accurate and Reliable Forecasting using Stochastic Differential Equations Peng Cui Zhijie Deng Wenbo Hu Jun Zhu UQCV 32 1 0 28 Mar 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng Xiao Yang Shizhen Xu Hang Su Jun Zhu BDL AAML 12 61 0 27 Mar 2021
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise Jannik Schmitt Stefan Roth UQCV 11 6 0 15 Mar 2021
Analytically Tractable Inference in Deep Neural Networks L. Nguyen J. Goulet TPM BDL 11 3 0 09 Mar 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 21 107 0 24 Feb 2021
Structured Dropout Variational Inference for Bayesian Neural Networks S. Nguyen Duong Nguyen Khai Nguyen Khoat Than Hung Bui Nhat Ho BDL DRL 6 7 0 16 Feb 2021
Tractable structured natural gradient descent using local parameterizations Wu Lin Frank Nielsen Mohammad Emtiyaz Khan Mark W. Schmidt 23 29 0 15 Feb 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard E. Turner Mark van der Wilk Laurence Aitchison BDL UQCV 64 137 0 12 Feb 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 24 46 0 12 Feb 2021
Bayesian Inference with Certifiable Adversarial Robustness Matthew Wicker Luca Laurenti A. Patané Zhoutong Chen Zheng-Wei Zhang Marta Z. Kwiatkowska AAML BDL 20 30 0 10 Feb 2021
Continual Lifelong Learning in Natural Language Processing: A Survey Magdalena Biesialska Katarzyna Biesialska Marta R. Costa-jussá KELM CLL 16 215 0 17 Dec 2020
All You Need is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran Simone Rossi Dimitrios Milios Maurizio Filippone OOD BDL 23 56 0 25 Nov 2020
Generalized Variational Continual Learning Noel Loo S. Swaroop Richard E. Turner BDL CLL 33 58 0 24 Nov 2020
Deep learning for biomedical photoacoustic imaging: A review J. Gröhl Melanie Schellenberg Kris K. Dreher Lena Maier-Hein 35 191 0 05 Nov 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 23 45 0 28 Oct 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 23 83 0 28 Oct 2020
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning Zhijie Deng Jun Zhu BDL 21 9 0 05 Oct 2020
Non-exponentially weighted aggregation: regret bounds for unbounded loss functions Pierre Alquier 22 18 0 07 Sep 2020
Improving predictions of Bayesian neural nets via local linearization Alexander Immer M. Korzepa Matthias Bauer BDL 6 11 0 19 Aug 2020
A statistical theory of cold posteriors in deep neural networks Laurence Aitchison UQCV BDL 9 67 0 13 Aug 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 14 102 0 25 Jul 2020
Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks Alexander Immer BDL 6 4 0 21 Jul 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray L. Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 13 609 0 14 Jul 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 25 169 0 16 Jun 2020
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks Kirill Bykov Marina M.-C. Höhne Klaus-Robert Muller Shinichi Nakajima Marius Kloft UQCV FAtt 27 31 0 16 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 38 100 0 15 Jun 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán Umang Bhatt T. Adel Adrian Weller José Miguel Hernández-Lobato UQCV BDL 40 111 0 11 Jun 2020
Revisiting Explicit Regularization in Neural Networks for Well-Calibrated Predictive Uncertainty Taejong Joo U. Chung BDL UQCV 6 0 0 11 Jun 2020
Implications of Human Irrationality for Reinforcement Learning Haiyang Chen H. Chang Andrew Howes 18 1 0 07 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 23 60 0 17 May 2020