A Survey on Bayesian Deep Learning

Cited by (246)

Items 101–200 of 246

1. Computational Super-Resolution: An Odyssey in Harnessing Priors to Enhance Optical Microscopy Resolution
   Wenfeng Tian, Riwang Chen, Liangyi Chen · 2025 · Analytical Chemistry
2. Network analysis of multivariate time series data in biological systems: methods and applications
   Hao Mei, Zhiyuan Wang, Hang Yang, Xiaoke Li, Yaqing Xu · 2025 · Briefings in Bioinformatics
3. Bayesian Neural Networks for Reversible Steganography
   Ching‐Chun Chang · 2022 · IEEE Access
4. PixelSeg: Pixel-by-Pixel Stochastic Semantic Segmentation for Ambiguous Medical Images
   Wei Zhang, Xiaohong Zhang, Sheng Huang, Yuting Lü, Kun Wang · 2022 · ACM International Conference on Multimedia (ACM MM)
5. A High-Speed and High-Efficiency Diverse Error Margin Write-Verify Scheme for an RRAM-Based Neuromorphic Hardware Accelerator
   Yudeng Lin, Jian-Shi Tang, Bin Gao, Qi Qin, Qingtian Zhang, H. Qian, Hua-Qiang Wu · 2023 · IEEE Transactions on Circuits and Systems - II - Express Briefs
6. Yet Another Effective Dendritic Neuron Model Based on the Activity of Excitation and Inhibition
   Yifei Yang, Xiaosi Li, Haotian Li, Chaofeng Zhang, Yuki Todo, Haichuan Yang · 2023 · Mathematics
7. Uncertainty Forecasting Model for Mountain Flood Based on Bayesian Deep Learning
   Songsong Wang, Ouguan Xu · 2024 · IEEE Access
8. Fuzzy Multimodal Learning for Trusted Cross-modal Retrieval
   Siyuan Duan, Yuan Sun, Dezhong Peng, Zheng Liu, Xiaomin Song, Peng Hu · 2025 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
9. Parameter estimation from quantum-jump data using neural networks
   Enrico Rinaldi, Manuel González Lastre, Sergio García Herreros, Shahnawaz Ahmed, Maryam Khanahmadi, Franco Nori, Carlos Sánchez Muñoz · 2024 · Quantum Science and Technology
10. Bayesian Deep Learning via Expectation Maximization and Turbo Deep Approximate Message Passing
    Wei Xu, An Liu, Yiting Zhang, Vincent K. N. Lau · 2024 · IEEE Transactions on Signal Processing
11. Hybrid deep learning and RSM modeling of diesel engine performance using TiO2 doped butanol and waste plastic oil blends
    Dr. K. Senthil Kumar, Ali B.M. Ali, Abdul Razak, Ali Eisa M. Anqi, Ali A. Rajhi, Addisu Frinjo Emma, Md Amir Khan · 2026 · Scientific Reports
12. A Bayesian Graph Neural Network for EEG Classification — A Win-Win on Performance and Interpretability
    Jing Wang, Xiaojun Ning, Wangjun Shi, Youfang Lin · 2023 · IEEE International Conference on Data Engineering (ICDE)
13. Secure AI Model Sharing: A Cryptographic Approach for Encrypted Model Exchange
    Bheema Shanker Neyigapula · 2024 · International Journal of Artificial Intelligence and Machine Learning
14. Opportunities and Challenges for Inverse Design of Nanostructures with Sequence Defined Macromolecules
    Wesley F. Reinhart, Antonia Statt · 2021 · Accounts of Materials Research
15. Hierarchically trusted evidential fusion method with consistency learning for multimodal language understanding
    Ying Yang, Yan-Qiu Yang, Gang Ren, Bengong Yu · 2025 · Knowledge-Based Systems
16. Bayesian Deep Learning for Fault Diagnosis of Induction Motors With Reduced Data Reliance and Improved Interpretability
    Zhanbiao Lai, Weiwen Peng, Guodong Feng, Meilin Pan · 2025 · IEEE Transactions on Energy Conversion
17. Bayesian deep learning framework for updating landslide susceptibility assessment based on epistemic uncertainty with InSAR augmented samples
    Chongzhi Chen, Baiyu Dong, Jingya Lin, Zhangquan Shen, Luming Fang, Yuhui Weng, Ke Wang · 2025 · Journal of Rock Mechanics and Geotechnical Engineering
18. Inductive Conformal Prediction for Harvest-Readiness Classification of Cauliflower Plants: A Comparative Study of Uncertainty Quantification Methods
    Mohamed Farag, Jana Kierdorf, Ribana Roscher · 2023 · IEEE International Conference on Computer Vision Workshops
19. An Interpretable Deep Bayesian Model for Facial Micro-Expression Recognition
    Chenfeng Wang, Xiaoguang Gao, Xinyu Li · 2023 · International Conference on Control and Robotics Engineering (ICCRE)
20. Introspective Robot Perception Using Smoothed Predictions from Bayesian Neural Networks
    Jianxiang Feng, Maximilian Durner, Zoltán-Csaba Márton, Ferenc Bálint-Benczédi, Rudolph Triebel · 2022 · Springer proceedings in advanced robotics
21. A Bayesian Neural ODE for a Lettuce Greenhouse
    Sjoerd Boersma, Xiaodong Cheng · 2024 · IEEE Conference on Control Technology and Applications (CCTA)
22. Integrating statistical design and inference: A roadmap for robust and trustworthy medical AI
    Qiaochu Wei, Miao Cui, Zehua Liu, Zhonghua Liu, Guoshuang Feng, Yi Li, David C. Christiani, Liming Li, Jingyuan Wang, Yuantao Hao et al. · 2025 · The Innovation Medicine
23. Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness
    Jun-Liang Lin, Ranganath Krishnan, Keyur Ranipa, Mahesh M. Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Kandemir · 2023 · IEEE International Symposium on Workload Characterization
24. Explaining Probabilistic Bayesian Neural Networks for Cybersecurity Intrusion Detection
    Tengfei Yang, Yuansong Qiao, Brian Lee · 2024 · IEEE Access
25. Software Reliability Prediction: A Machine Learning and Approximation Bayesian Inference Approach
    Shahrzad Oveisi, Ali Moeini, Sayeh Mirzaei, Mohammad Ali Farsi · 2022 · Quality and Reliability Engineering International
26. Perspectives: Comparison of deep learning segmentation models on biophysical and biomedical data
    J. Shepard Bryan, Pedro Pessoa, Meysam Tavakoli, Steve Pressé · 2025 · Biophysical Journal
27. Bayesian deep learning methods applied to diabetic retinopathy disease: a review
    Halbast Rashid Ismael, Masoud Muhammed Hassan · 2023 · Indonesian Journal of Electrical Engineering and Computer Science
28. An analysis of medical images using deep learning
    Ankur Jain, Muddada Murali Krishna, Sai Nitisha Tadiboina, Kapil Kumar Joshi, Yerrolla Chanti, K. Sai Krishna · 2023 · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
29. Machine learning prediction models for stroke-associated pneumonia:Meta-analysis
    Yi Cao, Xi Zeng, Yangyang Gou, Lu Yu, Dian Zhu, Hui Wang, Yan Dai, Jie Tian, Jian Liu, Peng Min · 2025 · Computers in Biology and Medicine
30. A probabilistic approximate logic for neuro-symbolic learning and reasoning
    Mark-Oliver Stehr, Minyoung Kim, Carolyn Talcott · 2021 · Journal of Logical and Algebraic Methods in Programming
31. Medical Image Segmentation Using Deep Learning Techniques: Advancement and Challenges
    Balasubramanian Gopinath, V. Vinay Kumar, Hitesh Kag, Kapil Kumar Joshi, Akshay Rajput, Dhiraj Kapila · 2023 · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
32. A Bayesian deep learning approach for rheological properties prediction of asphalt binders considering uncertainty of output
    Bongjun Ji, Sushmit Sharma Bhattarai, Il-Ho Na, Hyun Hwan Kim · 2023 · Construction and Building Materials
33. Gibbs sampling the posterior of neural networks
    Giovanni Piccioli, Emanuele Troiani, Lenka Zdeborová · 2024 · Journal of Physics A Mathematical and Theoretical
34. Bayesian Sparsification for Deep Neural Networks With Bayesian Model Reduction
    Dimitrije Marković, Karl John Friston, Stefan J. Kiebel · 2024 · IEEE Access
35. A Review on Bayesian Methods for Uncertainty Quantification in Machine Learning Models Enhancing Predictive Accuracy and Model Interpretability
    Moses Makuei Jiet, Prateek Verma, Aahash Kamble, Chetan Puri · 2024 · International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI)
36. Load Balancing Performance Optimization for LI-Fi/Wi-Fi HLR Access Points Using Particle Swarm Optimization and DL Algorithms
    2022 · International journal of intelligent engineering and systems
37. Multi-objective optimization in high-dimensional patent layout using deep Bayesian network and hybrid algorithm
    Minghua Wu, Wenwu Jiang · 2025 · Discover Computing
38. Confident Naturalness Explanation (CNE): A Framework to Explain and Assess Patterns Forming Naturalness
    Ahmed Emam, Mohamed Farag, Ribana Roscher · 2024 · IEEE Geoscience and Remote Sensing Letters
39. Multimodal Bayesian Networks for Automatic Skin Disease Diagnosis
    Yunqi He, Jiahe Liu, You Li, Hai Ming Zhou, Linglong Cai, Taimei Cui · 2024 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
40. Assessing human situation awareness reliability considering fatigue and mood using EEG data: A Bayesian neural network-Bayesian network approach
    Song Ding, Lunhu Hu, Xing Pan, Dujun Zuo, Liuwang Sun · 2025 · Reliability Engineering & System Safety
41. Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation
    Wenbo Hu, Xin Sun, Qiang Liu, Le Wu, Liang Wang · 2025 · IEEE Transactions on Knowledge and Data Engineering
42. Estimating Predictive Uncertainty in Gastrointestinal Polyp Segmentation
    Felicia Ly Jacobsen, Steven Alexander Hicks, Pål Halvorsen, Michael Alexander Riegler · 2022 · Proceedings - IEEE Symposium on Computer-Based Medical Systems
43. Safety-Aware Autonomous Systems : Preparing Robots for Life in the Real World
    Mattias Tiger · 2022 · Linköping studies in science and technology. Dissertations
44. Deep neural network uncertainty quantification for LArTPC reconstruction
    D. H. Koh, Aashwin Mishra, K. Terao · 2023 · Journal of Instrumentation
45. Uncertainty-Aware and Reliable Neural MIMO Receivers via Modular Bayesian Deep Learning
    Tomer Raviv, Sangwoo Park, Osvaldo Simeone, Nir Shlezinger · 2025 · IEEE Transactions on Vehicular Technology
46. Variational Connectionist Temporal Classification for Order-Preserving Sequence Modeling
    Zheng Nan, Ting Dang, Vidhyasaharan Sethu, Beena Ahmed · 2024 · IEEE International Conference on Acoustics Speech and Signal Processing
47. DeepTSW: An Urban Traffic Safety Warning Framework Based on Bayesian Deep Learning
    Guojiang Shen, Lintao Guan, Jiajia Tan, Xiangjie Kong · 2020 · Communications in computer and information science
48. Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
    Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
49. LogSE: An Uncertainty-Based Multi-Task Loss Function for Learning Two Regression Tasks
    Zeinab Ghasemi-Naraghi, Ahmad Nickabadi, Reza Safabakhsh · 2022 · JUCS - Journal of Universal Computer Science
50. Understanding uncertainty in deep learning builds confidence
    Jürgen Bajorath · 2022 · Artificial Intelligence in the Life Sciences
51. Classification of Imaging Artifacts in Synthetic Aperture Sonar With Bayesian Deep Learning
    Marko Orescanin, Derek R. Olson, Brian Harrington, Marc Geilhufe, Roy Edgar Hansen, Dalton Duvio, Narada Dilp Warakagoda · 2025 · IEEE Journal of Oceanic Engineering
52. Bayesian Deep Learning Meets Self-Attention: A Risk-Aware Approach to Advertisement Optimization
    Arti Jha, Ashutosh Bhatia, Kamlesh Tiwari · 2025 · IEEE Access
53. A Comparative Study of Bayesian Neural Networks and Machine Learning Based on COVID-19 Image Classification
    Cheng-Han Yu, Shuaizhou Wang · 2025 · Statistics and data science in imaging.
54. Concentration Inequalities and Optimal Number of Layers for Stochastic Deep Neural Networks
    Michele Caprio, Sayan Mukherjee · 2023 · IEEE Access
55. Mitigating Uncertainty in Document Classification
    Xuchao Zhang, Fanglan Chen, Chang‐Tien Lu, Naren Ramakrishnan · 2019 · arXiv (Cornell University)
56. Sampling-Free Learning of Bayesian Quantized Neural Networks
    Jiahao Su, Milan W. Cvitkovic, Furong Huang · 2019 · arXiv (Cornell University)
57. Uncertainty-aware Visual Analytics - Scope, Oppertunities and Challenges
    Robin G. C. Maack, Gerik Scheuermann, Hans Hagen, José Tiberio Hernández Peñaloza, Christina Gillmann · 2021 · Research Square
58. JaxSGMC: Modular stochastic gradient MCMC in JAX
    Stephan Thaler, Paul Fuchs, Ana Cukarska, Julija Zavadlav · 2024 · SoftwareX
59. Variational Bayesian Neural Networks via Resolution of Singularities
    Susan H. Wei, Edmund Lau · 2024 · Journal of Computational and Graphical Statistics
60. Unveiling the Shadows: DarkNET Traffic Detection Using Deep Learning Techniques
    Naors Y. Anad Alsaleem, Samah Fakhri Aziz · 2025
61. AIA: A Customized Multi-Core RISC-V SoC for Discrete Sampling Workloads in 16 nm
    Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst · 2025 · IEEE Journal of Solid-State Circuits
62. Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration
    Xinzhe Luo, Xin Wang, Linda G. Shapiro, Chun Yuan, Jianfeng Feng, Xiahai Zhuang · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
63. Hierarchical Bayesian Deep Learning for return on advertising spend prediction: A probabilistic approach to e-commerce advertising
    Arti Jha, Ashutosh Bhatia, Kamlesh Tiwari, Hari Mohan Pandey · 2025 · Engineering Applications of Artificial Intelligence
64. Robust Forward Surrogates for Free-Form Frequency Selective Surfaces With Uncertainty Quantification by Bayesian Deep Learning
    Erji Li, Enze Zhu, Siyuan He, Bao Wang, Qian Wang, Zhun Wei, Wen-Yan Yin · 2026 · IEEE Transactions on Antennas and Propagation
65. Data fusion in air pollution exposure assessment: Methods, applications, and future directions
    Yang Liu, Howard H. Chang, Joshua S. Fu · 2026 · Journal of the Air & Waste Management Association
66. Serendipity-Oriented Clustering Method for Recommender Systems Based on Collaborative Filtering
    Edip Şenyürek, Jasmin Kevrić · 2022 · Lecture notes in networks and systems
67. Efficient Parameter Learning of Bayesian Network with Latent Variables from High-Dimensional Data
    Xinran Wu, Xiang Chen, Kun Yue · 2023 · IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
68. Propagating variational model uncertainty for bioacoustic call label smoothing
    Georgios Rizos, Jenna Lawson, Simon Mitchell, Pranay Shah, Xin Wen, Cristina Banks-Leite, Robert M. Ewers, Björn Wolfgang Schuller · 2024 · Patterns
69. Effects of Binary Similarity Metrics in Recommender Systems for Jester Jokes Dataset
    Edip Şenyürek, Jasmin Kevrić · 2024 · Lecture notes in networks and systems
70. HCN-RLR-CAN: A novel human-computer negotiation model based on round-level recurrence and causal attention networks
    Jiahui Zhang, Xudong Luo, Xiaojun Xie · 2025 · Knowledge-Based Systems
71. Towards the Uncertainty Quantification of AI-Models in 6G Networks
    Irene P. Keramidi, Poulcheria Zervou, John Lakoumentas, Kostas Ramantas, Christos V. Verikoukis · 2024 · IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)
72. Detecting abrupt changes in missing time series data
    Maximilian Toller, Bernhard Claus Geiger, Roman Kern · 2025 · Information Sciences
73. The state of hybrid artificial intelligence for interstellar missions
    Alex A. Ellery · 2025 · Progress in Aerospace Sciences
74. Deep Variational Autoencoder-Based Parameter Learning of Bayesian Network With Multiple Latent Variables
    Xinran Wu, Kun Yue, Liang Duan, Hong-Bo Xie, Huashuai Liu · 2025 · IEEE Transactions on Artificial Intelligence
75. Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics
    Inass Sekkat, Gabriel Stoltz · 2021 · HAL
76. Unsupervised Bayesian Subpixel Mapping Autoencoder Network for Hyperspectral Images
    Yuan Fang, Yuxian Wang, Linlin Xu, Yujia Chen, Alexander K.C. Wong, David A. Clausi · 2023 · IEEE Transactions on Geoscience and Remote Sensing
77. Real-time Activation Pattern Monitoring and Uncertainty Characterisation in Image Classification
    Shenglin Wang, Peng Wang, Lyudmila S. Mihaylova, Matthew Hill · 2021 · International Conference on Information Fusion (FUSION)
78. Bayesian Contrastive Representation Learning for Dynamic Graph
    Zian Wu, Huijun Tang, Huan Liu · 2022 · IEEE Smart World Congress (SWC)
79. Retrieving Continuous-Time Event Sequences Using Neural Temporal Point Processes with Learnable Hashing
    Vinayak Gupta, Srikanta Bedathur, Abir De · 2024 · ACM Transactions on Intelligent Systems and Technology
80. Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian
    Songsong Wang, Ouguan Xu · 2025 · PLoS ONE
81. Underspecification and uncertainty in deep learning models: Is there a connection?
    Filipa M. M. Ramos Ferreira, Rosaldo J. F. Rossetti · 2025 · Neural Computing and Applications
82. Domain Experience and Expertise in Explainable AI Applications: A Bearing Fault Diagnosis Case Study
    Zibin Zhao, Michael Castelle, Çağatay Turkay · 2025 · Proceedings of the ACM on Human-Computer Interaction
83. Uncertainty-Aware Task Offloading via Federated PDNNs in Multi-Tier Fog Networks
    Hoa Tran‐Dang, Dong‐Seong Kim · 2025 · IEEE International Conference on Industrial Informatics (INDIN)
84. UA-UATD: An Uncertainty-Aware Underwater Acoustic Target Detection Strategy via Deep Evidential Learning
    Chaofan Ma, Zhongzhe Xiao, Min Huang · 2025 · IEEE International Conference on Computer and Communications (ICCC)
85. Self-Adaptive Swarm System (SASS)
    Qin Yang · 2021 · International Joint Conference on Artificial Intelligence
86. Statistical Relational Learning for Genomics Applications: A State-of-the-Art Review
    Marenglen Biba, Narasimha Rao Vajjhala · 2022 · Studies in big data
87. Impact of measurement error on deep neural networks for nuclear material accountancy
    Nathan Shoman, Tom L. Burr · 2022 · Nuclear Engineering and Design
88. Towards Visual Classification Under Class Ambiguity
    Viktor Kozák, Ján Mikula, Lukáš Bertl, Karel Košnar, Libor Přeučil · 2023 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
89. Bayesian Opportunities for Brain–Computer Interfaces: Enhancement of the Existing Classification Algorithms and Out-of-Domain Detection
    Egor I. Chetkin, Sergei L. Shishkin, Bogdan L. Kozyrskiy · 2023 · Algorithms
90. Res-EMSA: Adaptive Adjustment of Innovation Based on Efficient Multihead Self-Attention in GNSS/INS Tightly Integrated Navigation System
    Hongfu Xu, Haiyong Luo, Zijian Wu, Fang Zhao · 2024 · IEEE Geoscience and Remote Sensing Letters
91. Do Bayesian Neural Networks Weapon System Improve Predictive Maintenance?
    Michael L. Potter, Miru Jun · 2024 · Annual Reliability and Maintainability Symposium (RAMS)
92. Predictive Coding Networks and Inference Learning: Tutorial and Survey
    B.H. van Zwol, Ro Jefferson, Egon L. van den Broek · 2026 · ACM Computing Surveys
93. Learning transferable representations by topic guided graph adversarial network
    Zhengjue Wang, Zhihui Xin, Chiyu Chen, Hao Zhang, Yea‐Shuan Huang, Yunsong Li, Hongwei Liu, Bo Chen · 2025 · Signal Processing
94. Adaptive-AutoMO: A domain adaptive automated multiobjective neural network for reliable lesion malignancy prediction via digital breast tomosynthesis
    Xi Chen, Jiahuan Lv, Zeyu Wang, Genggeng Qin, Zhiguo Zhou · 2025 · Journal of Biomedical Informatics
95. Can we imitate stock price behavior to reinforcement learn option price?
    Xin Jin · 2021
96. Can we imitate stock price behavior to reinforcement learn option price?
    Xin Jin · 2021
97. A Model-Driven Engineering Approach to Machine Learning and Software Modeling.
    Armin Moin, Atta Badii, Stephan Günnemann · 2021 · arXiv (Cornell University)
98. Multi-Label Classification of Heterogeneous Underwater Soundscapes with Bayesian Deep Learning
    Marko Orescanin, Brandon Beckler, Andrew Pfau, Sabrina Atchley, Nicholas Villemez, John E. Joseph, Christopher W. Miller, Tetyana Margolina · 2022
99. Measuring Investor Learning in Private Markets: A Sequential LLM–Bayesian Analysis of Expert Network Calls
    Yidong Chai, Yanguang Liu, Xuan Tian, Jiaheng Xie, Yonghang Zhou · 2025 · SSRN Electronic Journal
100. Learning Probabilistic Programs Using Backpropagation
     Avi Pfeffer · 2017 · arXiv (Cornell University)