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
Variational Visual Question Answering Tobias Jan Wieczorek Nathalie Daun Mohammad Emtiyaz Khan Marcus Rohrbach OOD 29 0 0 14 May 2025
Efficient Membership Inference Attacks by Bayesian Neural Network Zhenlong Liu Wenyu Jiang Feng Zhou Hongxin Wei MIALM 66 1 0 10 Mar 2025
Uncertainty-Aware Decoding with Minimum Bayes Risk Nico Daheim Clara Meister Thomas Möllenhoff Iryna Gurevych 53 0 0 07 Mar 2025
Variational Bayesian Pseudo-Coreset Hyungi Lee S. Lee Juho Lee BDL 36 0 0 28 Feb 2025
Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes Richard Bergna Stefan Depeweg Sergio Calvo-Ordoñez Jonathan Plenk Alvaro Cartea Jose Miguel Hernandez-Lobato UQCV AI4CE 40 0 0 28 Feb 2025
Spectral-factorized Positive-definite Curvature Learning for NN Training Wu Lin Felix Dangel Runa Eschenhagen Juhan Bae Richard E. Turner Roger B. Grosse 47 0 0 10 Feb 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 63 0 0 03 Feb 2025
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems G. Nam Juho Lee 69 0 0 22 Nov 2024
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections M. Miani Hrittik Roy Søren Hauberg UQCV BDL 32 0 0 22 Oct 2024
A Bayesian Interpretation of Adaptive Low-Rank Adaptation Haolin Chen Philip N. Garner 47 1 0 16 Sep 2024
Function-Space MCMC for Bayesian Wide Neural Networks Lucia Pezzetti Stefano Favaro Stefano Peluchetti BDL 121 0 0 26 Aug 2024
EVCL: Elastic Variational Continual Learning with Weight Consolidation Hunar Batra Ronald Clark CLL 22 1 0 23 Jun 2024
A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou Benjamin Eysenbach Frank Nielsen Artur Dubrawski UQCV 38 2 0 16 Jun 2024
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks Tristan Cinquin Robert Bamler UQCV BDL 38 2 0 06 Jun 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 50 3 0 05 Jun 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 54 1 0 04 Jun 2024
Transitional Uncertainty with Layered Intermediate Predictions Ryan Benkert M. Prabhushankar Ghassan AlRegib 40 1 0 25 May 2024
Generalized Laplace Approximation Yinsong Chen Samson S. Yu Zhong Li Chee Peng Lim BDL 53 0 0 22 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 45 9 0 06 May 2024
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers Johann Schmidt Sebastian Stober 43 1 0 06 May 2024
Variational Stochastic Gradient Descent for Deep Neural Networks Haotian Chen Anna Kuzina Babak Esmaeili Jakub M. Tomczak 41 0 0 09 Apr 2024
EventSleep: Sleep Activity Recognition with Event Cameras Carlos Plou Nerea Gallego Alberto Sabater Eduardo Montijano Pablo Urcola Luis Montesano Ruben Martinez-Cantin Ana C. Murillo 29 1 0 02 Apr 2024
A Unified and General Framework for Continual Learning Zhenyi Wang Yan Li Li Shen Heng-Chiao Huang CLL 32 17 0 20 Mar 2024
Function-space Parameterization of Neural Networks for Sequential Learning Aidan Scannell Riccardo Mereu Paul E. Chang Ella Tamir J. Pajarinen Arno Solin BDL 34 5 0 16 Mar 2024
Variational Learning is Effective for Large Deep Networks Yuesong Shen Nico Daheim Bai Cong Peter Nickl Gian Maria Marconi ... Rio Yokota Iryna Gurevych Daniel Cremers Mohammad Emtiyaz Khan Thomas Möllenhoff 35 22 0 27 Feb 2024
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods Jiaxin Zhang Kamalika Das Kumar Sricharan UQCV 27 0 0 20 Feb 2024
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts Emanuele Marconato Samuele Bortolotti Emile van Krieken Antonio Vergari Andrea Passerini Stefano Teso 41 18 0 19 Feb 2024
Rethinking Test-time Likelihood: The Likelihood Path Principle and Its Application to OOD Detection Sicong Huang Jiawei He Kry Yik-Chau Lui 22 0 0 10 Jan 2024
Bayesian Intrinsic Groupwise Image Registration: Unsupervised Disentanglement of Anatomy and Geometry Xinzhe Luo Xin Wang Linda Shapiro Chun Yuan Jianfeng Feng Xiahai Zhuang 26 0 0 04 Jan 2024
Tractable Function-Space Variational Inference in Bayesian Neural Networks Tim G. J. Rudner Zonghao Chen Yee Whye Teh Y. Gal 80 39 0 28 Dec 2023
A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation Yu Duan M. Eaton Michael Bluck 11 0 0 13 Dec 2023
Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC Wu Lin Felix Dangel Runa Eschenhagen Kirill Neklyudov Agustinus Kristiadi Richard E. Turner Alireza Makhzani 22 3 0 09 Dec 2023
Perspectives on the State and Future of Deep Learning - 2023 Micah Goldblum A. Anandkumar Richard Baraniuk Tom Goldstein Kyunghyun Cho Zachary Chase Lipton Melanie Mitchell Preetum Nakkiran Max Welling Andrew Gordon Wilson 53 4 0 07 Dec 2023
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 21 0 0 06 Dec 2023
Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks Alexander M¨ollers Alexander Immer Elvin Isufi Vincent Fortuin SSL BDL UQCV 21 1 0 30 Nov 2023
Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission Jianfeng He Linlin Yu Shuo Lei Chang-Tien Lu Feng Chen UQLM 20 8 0 15 Nov 2023
Model Merging by Uncertainty-Based Gradient Matching Nico Daheim Thomas Möllenhoff E. Ponti Iryna Gurevych Mohammad Emtiyaz Khan MoMe FedML 32 43 0 19 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 24 2 0 16 Oct 2023
Implicit Variational Inference for High-Dimensional Posteriors Anshuk Uppal Kristoffer Stensbo-Smidt Wouter Boomsma J. Frellsen BDL 15 1 0 10 Oct 2023
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods Ling Huang S. Ruan Yucheng Xing Mengling Feng 33 20 0 09 Oct 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
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks Nick Pepper George De Ath Marc Thomas Richard Everson T. Dodwell 27 0 0 26 Sep 2023
Improving Transferability of Adversarial Examples via Bayesian Attacks Qizhang Li Yiwen Guo Xiaochen Yang W. Zuo Hao Chen AAML BDL 26 2 0 21 Jul 2023
Adversarial Robustness Certification for Bayesian Neural Networks Matthew Wicker A. Patané Luca Laurenti Marta Z. Kwiatkowska AAML 23 3 0 23 Jun 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift Florian Seligmann P. Becker Michael Volpp Gerhard Neumann UQCV 19 14 0 21 Jun 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming Steven Adams A. Patané Morteza Lahijanian Luca Laurenti AAML 84 7 0 19 Jun 2023
BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagation Valentin Bieri Paul Streli B. U. Demirel Christian Holz 16 8 0 13 Jun 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 28 6 0 26 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 30 75 0 07 May 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization Agustinus Kristiadi Alexander Immer Runa Eschenhagen Vincent Fortuin BDL UQCV 15 8 0 17 Apr 2023