Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users

14 July 2020

Laurent Valentin Jospin

Papers citing "Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users"

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Title
LAPSO: A Unified Optimization View for Learning-Augmented Power System Operations Wangkun Xu Zhongda Chu Fei Teng 48 0 0 08 May 2025
CoCoAFusE: Beyond Mixtures of Experts via Model Fusion Aurelio Raffa Ugolini M. Tanelli Valentina Breschi MoE 24 0 0 02 May 2025
A Langevin sampling algorithm inspired by the Adam optimizer B. Leimkuhler René Lohmann P. Whalley 79 0 0 26 Apr 2025
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities Jimmy Huy Tran T. S. Kleppe BDL 45 0 0 25 Apr 2025
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification Mohaddeseh Chegini Ali Mahloojifar BDL UQCV 78 0 0 23 Apr 2025
Decentralized Collective World Model for Emergent Communication and Coordination Kentaro Nomura Tatsuya Aoki Tadahiro Taniguchi Takato Horii 72 0 0 04 Apr 2025
Uncertainty-aware Bayesian machine learning modelling of land cover classification Samuel Bilson Anna Pustogvar UQCV 97 1 0 27 Mar 2025
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model Mohaddeseh Chegini Ali Mahloojifar 75 1 0 18 Mar 2025
A Unified Evaluation Framework for Epistemic Predictions Shireen Kudukkil Manchingal Muhammad Mubashar Kaizheng Wang Fabio Cuzzolin UQCV 67 2 0 28 Jan 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 92 12 0 28 Jan 2025
The Curious Case of Arbitrariness in Machine Learning Prakhar Ganesh Afaf Taik G. Farnadi 61 2 0 28 Jan 2025
Analog Bayesian neural networks are insensitive to the shape of the weight distribution Ravi G. Patel T. Xiao S. Agarwal C. Bennett 38 0 0 09 Jan 2025
Legitimate ground-truth-free metrics for deep uncertainty classification scoring Arthur Pignet Chiara Regniez John Klein 72 1 0 30 Oct 2024
Generative Edge Detection with Stable Diffusion Caixia Zhou Yaping Huang Mochu Xiang Jiahui Ren Haibin Ling Jing Zhang 59 0 0 04 Oct 2024
SEF: A Method for Computing Prediction Intervals by Shifting the Error Function in Neural Networks E. V. Aretos D. G. Sotiropoulos 25 0 0 08 Sep 2024
Joint Segmentation and Image Reconstruction with Error Prediction in Photoacoustic Imaging using Deep Learning Ruibo Shang Geoffrey P. Luke Matthew O'Donnell UQCV 37 0 0 02 Jul 2024
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods Andrej Tschalzev Paul Nitschke Lukas Kirchdorfer Stefan Lüdtke Christian Bartelt Heiner Stuckenschmidt 36 0 0 01 Jul 2024
Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA Zehuan Zhang Hongxiang Fan Hao Mark Chen Lukasz Dudziak Wayne Luk BDL 40 0 0 23 Jun 2024
Building Continuous Quantum-Classical Bayesian Neural Networks for a Classical Clinical Dataset Alona Sakhnenko Julian Sikora J. M. Lorenz 39 0 0 10 Jun 2024
Cycles of Thought: Measuring LLM Confidence through Stable Explanations Evan Becker Stefano Soatto 45 6 0 05 Jun 2024
Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks Alan A. Lahoud Erik Schaffernicht J. A. Stork UQCV 30 0 0 05 Jun 2024
CONFINE: Conformal Prediction for Interpretable Neural Networks Linhui Huang S. Lala N. Jha 68 2 0 01 Jun 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 0 27 May 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification Kaizheng Wang Fabio Cuzzolin Keivan K1 Shariatmadar David Moens Hans Hallez UQCV BDL 85 0 0 23 May 2024
Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression Yuxuan Yin Xiaoxiao Wang Rebecca Chen Chen He Peng Li 18 1 0 03 May 2024
Uncertainty Estimation in Multi-Agent Distributed Learning for AI-Enabled Edge Devices Gleb I. Radchenko Victoria Andrea Fill 40 1 0 14 Mar 2024
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation Yidong Zhao João Tourais Iain Pierce Christian Nitsche T. Treibel Sebastian Weingartner Artur M. Schweidtmann Qian Tao BDL UQCV 43 5 0 04 Mar 2024
A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties D. Schodt Ryan Brown Michael Merritt Samuel Park Delsin Menolascino M. Peot BDL UQCV UD 32 1 0 22 Feb 2024
Assessing Uncertainty Estimation Methods for 3D Image Segmentation under Distribution Shifts Masoumeh Javanbakhat Md Tasnimul Hasan Cristoph Lippert UQCV OOD 26 1 0 10 Feb 2024
Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks Youngkyoung Bae Seungwoong Ha Hawoong Jeong 73 2 0 02 Feb 2024
Bayesian Inference Accelerator for Spiking Neural Networks Prabodh Katti Anagha Nimbekar Chen Li Amit Acharyya Bashir M. Al-Hashimi Bipin Rajendran TPM 15 2 0 27 Jan 2024
Inadequacy of common stochastic neural networks for reliable clinical decision support Adrian Lindenmeyer Malte Blattmann S. Franke Thomas Neumuth Daniel Schneider BDL 35 1 0 24 Jan 2024
Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification Simon W. McKnight Aidan O. T. Hogg Vincent W. Neo Patrick A. Naylor 19 1 0 28 Dec 2023
Favour: FAst Variance Operator for Uncertainty Rating Thomas Dybdahl Ahle Sahar Karimi Peter Tak Peter Tang BDL 27 0 0 21 Nov 2023
Spatial Bayesian Neural Networks A. Zammit‐Mangion Michael D. Kaminski Ba-Hien Tran Maurizio Filippone Noel Cressie BDL 18 7 0 16 Nov 2023
From Pointwise to Powerhouse: Initialising Neural Networks with Generative Models Christian Harder Moritz Fuchs Yuri Tolkach Anirban Mukhopadhyay 30 0 0 25 Oct 2023
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions Shiyu Shen Bin Pan Tianyang Shi Tao Li Zhenwei Shi BDL OOD 35 1 0 25 Oct 2023
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
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks Nick Pepper George De Ath Marc Thomas Richard Everson T. Dodwell 35 0 0 26 Sep 2023
Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices Elizaveta Kostenok D. Cherniavskii Alexey Zaytsev 56 5 0 22 Aug 2023
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation S. Landgraf Markus Hillemann Kira Wursthorn Markus Ulrich SSeg UQCV 26 6 0 19 Jul 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 35 0 0 10 Jun 2023
Gibbs Sampling the Posterior of Neural Networks Giovanni Piccioli Emanuele Troiani Lenka Zdeborová 41 2 0 05 Jun 2023
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty Anshul Nayak A. Eskandarian Zachary R. Doerzaph P. Ghorai 35 4 0 26 May 2023
Bayesian Renormalization D. Berman Marc S. Klinger A. G. Stapleton 35 16 0 17 May 2023
Noise robust neural network architecture Yunuo Xiong Hongwei Xiong 14 1 0 16 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 33 75 0 07 May 2023
Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network Rebecca S Stone Nishant Ravikumar A. Bulpitt David C. Hogg BDL 36 0 0 29 Mar 2023
Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering Xu Zhang Wenpeng Li Yunfeng Shao Yinchuan Li FedML 24 4 0 08 Mar 2023
Machine Learning with High-Cardinality Categorical Features in Actuarial Applications Benjamin Avanzi G. Taylor Melantha Wang Bernard Wong 22 12 0 30 Jan 2023