Bayesian Layers: A Module for Neural Network Uncertainty

10 December 2018

Dustin Tran

Michael W. Dusenberry

Papers citing "Bayesian Layers: A Module for Neural Network Uncertainty"

31 / 31 papers shown

Title
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review Toghrul Abbasli Kentaroh Toyoda Yuan Wang Leon Witt Muhammad Asif Ali Yukai Miao Dan Li Qingsong Wei UQCV 94 0 0 25 Apr 2025
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models Yibin Wang Haizhou Shi Ligong Han Dimitris N. Metaxas Hao Wang BDL UQLM 116 7 0 28 Jan 2025
Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads Andrea Vaiuso Gabriele Immordino Marcello Righi A. Ronch AI4CE 48 0 0 08 Jul 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov Hampus Linander UQCV 36 14 0 19 Feb 2024
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods Ling Huang S. Ruan Yucheng Xing Mengling Feng 41 20 0 09 Oct 2023
Block-local learning with probabilistic latent representations David Kappel Khaleelulla Khan Nazeer Cabrel Teguemne Fokam Christian Mayr Anand Subramoney 24 4 0 24 May 2023
Bayesian Neural Network Language Modeling for Speech Recognition Boyang Xue Shoukang Hu Junhao Xu Mengzhe Geng Xunying Liu Helen M. Meng UQCV BDL 44 14 0 28 Aug 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A. Maraval Matthieu Zimmer Antoine Grosnit Rasul Tutunov Jun Wang H. Ammar 30 2 0 27 May 2022
Application of belief functions to medical image segmentation: A review Ling Huang S. Ruan Thierry Denoeux EDL MedIm 27 30 0 03 May 2022
Hyperbolic Image Segmentation Mina Ghadimi Atigh Julian Schoep Erman Acar Nanne van Noord Pascal Mettes 48 86 0 11 Mar 2022
Lymphoma segmentation from 3D PET-CT images using a deep evidential network Ling Huang S. Ruan P. Decazes Thierry Denoeux 3DPC MedIm 41 37 0 31 Jan 2022
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies Vivian Lai Chacha Chen Q. V. Liao Alison Smith-Renner Chenhao Tan 33 186 0 21 Dec 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 34 9 0 08 Oct 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 31 6 0 01 Oct 2021
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations Jianxiong Shen Adria Ruiz Antonio Agudo Francesc Moreno-Noguer BDL 36 68 0 05 Sep 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 20 7 0 30 Jun 2021
Graceful Degradation and Related Fields J. Dymond 31 4 0 21 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression David Rügamer Chris Kolb Cornelius Fritz Florian Pfisterer Philipp Kopper ... Dominik Thalmeier Philipp F. M. Baumann Lucas Kook Nadja Klein Christian L. Müller BDL 16 19 0 06 Apr 2021
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems Martin Mladenov Chih-Wei Hsu Vihan Jain Eugene Ie Christopher Colby Nicolas Mayoraz H. Pham Dustin Tran Ivan Vendrov Craig Boutilier BDL 15 31 0 14 Mar 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference Felix Leibfried Vincent Dutordoir S. T. John N. Durrande GP 42 49 0 27 Dec 2020
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data Chacha Chen Junjie Liang Fenglong Ma Lucas Glass Jimeng Sun Cao Xiao 21 26 0 22 Oct 2020
Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment Florin-Cristian Ghesu Bogdan Georgescu Awais Mansoor Y. Yoo Eli Gibson ... Ramandeep Singh S. Digumarthy M. Kalra Sasa Grbic Dorin Comaniciu UQCV EDL 23 55 0 08 Jul 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 33 204 0 24 Jun 2020
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study Himanshu Sharma Elise Jennings BDL 27 3 0 23 May 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 36 6 0 07 Jan 2020
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation Amir Atapour-Abarghouei Stephen Bonner A. Mcgough 29 7 0 19 Aug 2019
Analyzing the Role of Model Uncertainty for Electronic Health Records Michael W. Dusenberry Dustin Tran Edward Choi Jonas Kemp Jeremy Nixon Ghassen Jerfel Katherine A. Heller Andrew M. Dai 15 117 0 10 Jun 2019
Discrete Flows: Invertible Generative Models of Discrete Data Dustin Tran Keyon Vafa Kumar Krishna Agrawal Laurent Dinh Ben Poole DRL 24 114 0 24 May 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 268 0 13 Jun 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015