Probabilistic Backpropagation for Scalable Learning of Bayesian Neural
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Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks

18 February 2015

José Miguel Hernández-Lobato

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Papers citing "Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks"

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Title
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective Xueqiong Yuan Jipeng Li E. Kuruoglu UQCV BDL 130 0 0 21 Jan 2025
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing David Perera Victor Letzelter Théo Mariotte Adrien Cortés Mickaël Chen S. Essid Ga¨el Richard 156 4 0 20 Jan 2025
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi Yibin Wang Ligong Han Huatian Zhang Hao Wang UQCV 199 2 0 07 Dec 2024
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 265 1 0 25 Nov 2024
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 90 1 0 30 Oct 2024
Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown Xingzhou Lou Dong Yan Wei Shen Yuzi Yan Jian Xie Junge Zhang 189 28 0 01 Oct 2024
Gradient-free variational learning with conditional mixture networks Conor Heins Hao Wu Dimitrije Marković Alexander Tschantz Jeff Beck Christopher L. Buckley BDL 74 3 0 29 Aug 2024
Enabling Uncertainty Estimation in Iterative Neural Networks Nikita Durasov Doruk Öner Jonathan Donier Hieu M. Le Pascal Fua UQCV 177 9 0 25 Mar 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 171 28 0 07 Feb 2024
Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction Qinghui Liu E. Fuster-García I. T. Hovden Donatas Sederevičius Karoline Skogen ... Till Schellhorn P. Brandal A. Bjørnerud K. Emblem Kyrre Eeg Emblem 89 3 0 11 Sep 2023
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Yue Liu P. Varshney Basel Alomair AAML 139 47 0 16 Mar 2020
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 113 44 0 23 Oct 2019
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server Leonard Hasenclever Stefan Webb Thibaut Lienart Sebastian J. Vollmer Balaji Lakshminarayanan Charles Blundell Yee Whye Teh BDL 152 70 0 31 Dec 2015
Deep Image: Scaling up Image Recognition Ren Wu Shengen Yan Yi Shan Qingqing Dang Gang Sun VLM 70 374 0 13 Jan 2015
Deep Speech: Scaling up end-to-end speech recognition Awni Y. Hannun Carl Case Jared Casper Bryan Catanzaro G. Diamos ... R. Prenger S. Satheesh Shubho Sengupta Adam Coates A. Ng 186 2,128 0 17 Dec 2014
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 443 20,584 0 10 Sep 2014
Expectation Propagation for Neural Networks with Sparsity-promoting Priors Pasi Jylänki A. Nummenmaa Aki Vehtari 69 36 0 27 Mar 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 369 7,957 0 13 Jun 2012