Priors in Bayesian Deep Learning: A Review

14 May 2021

Papers citing "Priors in Bayesian Deep Learning: A Review"

50 / 83 papers shown

Title
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review Chengmin Zhou Ville Kyrki P. Fränti Laura Ruotsalainen BDL AI4CE 27 0 0 12 May 2025
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know Shireen Kudukkil Manchingal Fabio Cuzzolin 42 0 0 08 May 2025
On the Role of Priors in Bayesian Causal Learning Bernhard C. Geiger Roman Kern CML 32 0 0 02 Apr 2025
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 34 0 0 07 Oct 2024
Bayes-CATSI: A variational Bayesian deep learning framework for medical time series data imputation Omkar Kulkarni Rohitash Chandra CML AI4TS BDL 27 0 0 01 Oct 2024
Empowering Bayesian Neural Networks with Functional Priors through Anchored Ensembling for Mechanics Surrogate Modeling Applications Javad Ghorbanian Nicholas Casaprima Audrey Olivier 26 0 0 08 Sep 2024
Low-Budget Simulation-Based Inference with Bayesian Neural Networks Arnaud Delaunoy Maxence de la Brassinne Bonardeaux S. Mishra-Sharma Gilles Louppe 33 2 0 27 Aug 2024
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection Steven Adams A. Patané Morteza Lahijanian Luca Laurenti BDL 23 1 0 26 Jul 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference Jian Xu Delu Zeng John Paisley DiffM 24 1 0 24 Jul 2024
On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss Mohammed Fellaji Frédéric Pennerath Brieuc Conan-Guez Miguel Couceiro UQCV 27 1 0 16 Jul 2024
Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modeling Abril Corona-Figueroa Hubert P. H. Shum Chris G. Willcocks 16 0 0 26 Jun 2024
Assessment of Uncertainty Quantification in Universal Differential Equations Nina Schmid David Fernandes del Pozo Willem Waegeman Jan Hasenauer AI4CE 28 1 0 13 Jun 2024
Domain Generalization Guided by Large-Scale Pre-Trained Priors Zongbin Wang Bin Pan Shiyu Shen Tianyang Shi Zhenwei Shi AI4CE 21 0 0 09 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 43 1 0 31 May 2024
Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision Stefan Dietrich Julian Rodemann Christoph Jansen BDL 27 5 0 24 May 2024
Gaussian Stochastic Weight Averaging for Bayesian Low-Rank Adaptation of Large Language Models Emre Onal Klemens Flöge Emma Caldwell A. Sheverdin Vincent Fortuin UQCV BDL 32 9 0 06 May 2024
The Landscape of Unfolding with Machine Learning Nathan Huetsch Javier Marino Villadamigo Alexander Shmakov S. Diefenbacher Vinicius Mikuni ... Kevin Greif Benjamin Nachman D. Whiteson A. Butter Tilman Plehn 24 17 0 29 Apr 2024
Making Better Use of Unlabelled Data in Bayesian Active Learning Freddie Bickford-Smith Adam Foster Tom Rainforth 20 3 0 26 Apr 2024
Season combinatorial intervention predictions with Salt & Peper Thomas Gaudelet Alice Del Vecchio Eli M. Carrami Juliana Cudini Chantriolnt-Andreas Kapourani Caroline Uhler Lindsay Edwards 33 7 0 25 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 51 23 0 17 Apr 2024
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models Saurav Jha Dong Gong Lina Yao CLIP VLM 33 7 0 28 Mar 2024
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling Hyungi Lee G. Nam Edwin Fong Juho Lee BDL 20 5 0 12 Mar 2024
Bayesian Diffusion Models for 3D Shape Reconstruction Haiyang Xu Yu Lei Zeyuan Chen Xiang Zhang Yue Zhao Yilin Wang Zhuowen Tu DiffM 24 8 0 11 Mar 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Bayesian Neural Networks with Domain Knowledge Priors Dylan Sam Rattana Pukdee Daniel P. Jeong Yewon Byun J. Zico Kolter BDL UQCV 27 9 0 20 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 35 27 0 01 Feb 2024
Forecasting VIX using Bayesian Deep Learning Héctor J. Hortúa Andrés Mora-Valencia BDL OOD 15 4 0 30 Jan 2024
Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks Alexander M¨ollers Alexander Immer Elvin Isufi Vincent Fortuin SSL BDL UQCV 16 1 0 30 Nov 2023
$Improved identification accuracy in equation learning via comprehensive $\boldsymbol{R^2}$-elimination and Bayesian model selection$ Improved identification accuracy in equation learning via comprehensive $\boldsymbol{R^2}$ -elimination and Bayesian model selection Daniel Nickelsen B. Bah 22 0 0 22 Nov 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 54 18 0 28 Sep 2023
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantization Christopher Subia-Waud S. Dasmahapatra UQCV MQ 8 0 0 24 Sep 2023
Bayesian sparsification for deep neural networks with Bayesian model reduction Dimitrije Marković K. Friston S. Kiebel BDL UQCV 23 1 0 21 Sep 2023
Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing Flows Jian Xu Shian Du Junmei Yang Xinghao Ding John Paisley Delu Zeng 13 0 0 17 Sep 2023
Stochastic automatic differentiation for Monte Carlo processes Guilherme Catumba A. Ramos B. Zaldívar 13 7 0 28 Jul 2023
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks Dominik Schnaus Jongseok Lee Daniel Cremers Rudolph Triebel UQCV BDL 33 1 0 15 Jul 2023
Function-Space Regularization for Deep Bayesian Classification J. Lin Joe Watson Pascal Klink Jan Peters UQCV BDL 25 1 0 12 Jul 2023
Solution of physics-based inverse problems using conditional generative adversarial networks with full gradient penalty Deep Ray Javier Murgoitio-Esandi Agnimitra Dasgupta Assad A. Oberai GAN 13 13 0 08 Jun 2023
Is novelty predictable? Clara Fannjiang Jennifer Listgarten AI4CE 10 14 0 01 Jun 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 19 6 0 26 May 2023
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance Jorge Loría A. Bhadra UQCV BDL 19 1 0 18 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 18 75 0 07 May 2023
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows Lars Skaaret-Lund G. Storvik A. Hubin BDL UQCV 28 3 0 05 May 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization Agustinus Kristiadi Alexander Immer Runa Eschenhagen Vincent Fortuin BDL UQCV 13 8 0 17 Apr 2023
Incorporating Unlabelled Data into Bayesian Neural Networks Mrinank Sharma Tom Rainforth Yee Whye Teh Vincent Fortuin SSL UQCV BDL 32 9 0 04 Apr 2023
Bayesian neural networks via MCMC: a Python-based tutorial Rohitash Chandra Royce Chen Joshua Simmons BDL 11 9 0 02 Apr 2023
Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shift Francisco Pérez-Galarce K. Pichara P. Huijse M. Catelán D. Méry 15 0 0 12 Mar 2023
Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference Amine M. Remita Golrokh Vitae Abdoulaye Baniré Diallo BDL 11 0 0 06 Feb 2023
Data Subsampling for Bayesian Neural Networks Eiji Kawasaki M. Holzmann BDL 14 1 0 17 Oct 2022
Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization Jim Beckers Bart Van Erp Ziyue Zhao K. Kondrashov Bert De Vries AAML 8 5 0 17 Oct 2022
Efficient Bayesian Updates for Deep Learning via Laplace Approximations Denis Huseljic M. Herde Lukas Rauch Paul Hahn Zhixin Huang D. Kottke S. Vogt Bernhard Sick BDL 11 0 0 12 Oct 2022