Functional Variational Bayesian Neural Networks

14 March 2019

Papers citing "Functional Variational Bayesian Neural Networks"

50 / 85 papers shown

Title
Revisiting Unbiased Implicit Variational Inference Tobias Pielok Bernd Bischl David Rügamer BDL 83 0 0 04 Jun 2025
Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know' Shireen Kudukkil Manchingal Andrew Bradley Julian F. P. Kooij Keivan K1 Shariatmadar Neil Yorke-Smith Fabio Cuzzolin 165 1 0 08 May 2025
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference Jasmeet Kaur BDL UQCV 124 0 0 15 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 114 0 0 25 Feb 2025
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks Tristan Cinquin Robert Bamler UQCV BDL 132 2 0 06 Jun 2024
Continual Learning via Sequential Function-Space Variational Inference Tim G. J. Rudner Freddie Bickford-Smith Qixuan Feng Yee Whye Teh Y. Gal 74 42 0 28 Dec 2023
Density Uncertainty Layers for Reliable Uncertainty Estimation Yookoon Park David M. Blei UQCV BDL 58 2 0 21 Jun 2023
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 66 7 0 19 Feb 2023
Piecewise Deterministic Markov Processes for Bayesian Neural Networks Ethan Goan Dimitri Perrin Kerrie Mengersen Clinton Fookes 67 0 0 17 Feb 2023
Diffusion Generative Models in Infinite Dimensions Gavin Kerrigan Justin Ley Padhraic Smyth DiffM 114 35 0 01 Dec 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 84 57 0 11 Nov 2022
Amortized Variational Inference: A Systematic Review Ankush Ganguly Sanjana Jain Ukrit Watchareeruetai 88 17 0 22 Sep 2022
On the detrimental effect of invariances in the likelihood for variational inference Richard Kurle R. Herbrich Tim Januschowski Bernie Wang Jan Gasthaus 67 10 0 15 Sep 2022
Correcting Model Bias with Sparse Implicit Processes Simón Rodríguez Santana Luis A. Ortega Andrés Daniel Hernández-Lobato B. Zaldívar BDL 51 1 0 21 Jul 2022
Deep Learning and Symbolic Regression for Discovering Parametric Equations Michael Zhang Samuel Kim Peter Y. Lu M. Soljavcić 72 21 0 01 Jul 2022
Tackling covariate shift with node-based Bayesian neural networks Trung Trinh Markus Heinonen Luigi Acerbi Samuel Kaski BDL UQCV 63 6 0 06 Jun 2022
Deep Ensemble as a Gaussian Process Approximate Posterior Zhijie Deng Feng Zhou Jianfei Chen Guoqiang Wu Jun Zhu UQCV 41 5 0 30 Apr 2022
Dynamic Combination of Heterogeneous Models for Hierarchical Time Series Xing Han Jing Hu Joydeep Ghosh AI4TS 78 2 0 22 Dec 2021
Periodic Activation Functions Induce Stationarity Lassi Meronen Martin Trapp Arno Solin BDL 91 21 0 26 Oct 2021
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices Jan Povala Ieva Kazlauskaite Eky Febrianto F. Cirak Mark Girolami 91 23 0 22 Oct 2021
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 94 22 0 09 Oct 2021
Training on Test Data with Bayesian Adaptation for Covariate Shift Aurick Zhou Sergey Levine OOD TTA 112 13 0 27 Sep 2021
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 151 46 0 16 Sep 2021
A variational approximate posterior for the deep Wishart process Sebastian W. Ober Laurence Aitchison BDL 42 11 0 21 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 242 1,177 0 07 Jul 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 129 101 0 22 Jun 2021
Model Selection for Bayesian Autoencoders Ba-Hien Tran Simone Rossi Dimitrios Milios Pietro Michiardi Edwin V. Bonilla Maurizio Filippone BDL 82 13 0 11 Jun 2021
Meta-Learning Reliable Priors in the Function Space Jonas Rothfuss Dominique Heyn Jinfan Chen Andreas Krause 84 28 0 06 Jun 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights H. Ritter Martin Kukla Chen Zhang Yingzhen Li UQCV BDL 90 17 0 30 May 2021
Can we imitate the principal investor's behavior to learn option price? Xin Jin 49 0 0 24 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 137 134 0 14 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 387 17 0 23 Apr 2021
Accurate and Reliable Forecasting using Stochastic Differential Equations Peng Cui Zhijie Deng Wenbo Hu Jun Zhu UQCV 75 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 81 62 0 27 Mar 2021
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series Xing Han S. Dasgupta Joydeep Ghosh AI4TS 79 34 0 25 Feb 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 133 141 0 12 Feb 2021
Continuous-Time Model-Based Reinforcement Learning Çağatay Yıldız Markus Heinonen Harri Lähdesmäki OffRL 71 58 0 09 Feb 2021
The Gaussian Neural Process W. Bruinsma James Requeima Andrew Y. K. Foong Jonathan Gordon Richard Turner BDL 77 29 0 10 Jan 2021
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks Arno Blaas Stephen J. Roberts BDL AAML 85 2 0 07 Jan 2021
An Active Learning Method for Diabetic Retinopathy Classification with Uncertainty Quantification Muhammad Ahtazaz Ahsan A. Qayyum Junaid Qadir Adeel Razi BDL 93 20 0 24 Dec 2020
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch BDL UQCV 94 27 0 04 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 77 61 0 25 Nov 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 369 1,947 0 12 Nov 2020
Sample-efficient reinforcement learning using deep Gaussian processes Charles W. L. Gadd Markus Heinonen Harri Lähdesmäki Samuel Kaski GP BDL 64 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 130 86 0 28 Oct 2020
Scalable Bayesian neural networks by layer-wise input augmentation Trung Trinh Samuel Kaski Markus Heinonen UQCV BDL 36 3 0 26 Oct 2020
Out-of-distribution detection for regression tasks: parameter versus predictor entropy Y. Pequignot Mathieu Alain Patrick Dallaire Alireza Yeganehparast Pascal Germain Josée Desharnais Franccois Laviolette OODD 36 2 0 24 Oct 2020
Incorporating Interpretable Output Constraints in Bayesian Neural Networks Wanqian Yang Lars Lorch Moritz Graule Himabindu Lakkaraju Finale Doshi-Velez UQCV BDL 68 17 0 21 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning Lassi Meronen Christabella Irwanto Arno Solin UQCV BDL 54 19 0 19 Oct 2020
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence Agustinus Kristiadi Matthias Hein Philipp Hennig BDL 63 9 0 06 Oct 2020