An Introduction to Variational Autoencoders

Cited by (1,002)

Items 701–800 of 1,002

1. Generating Realistic Tabular Data with Large Language Models
   Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh · 2024 · Proceedings
2. Deep Graph Convolutional Autoencoder With Conditional Normalizing Flow for Power Distribution Systems Fault Classification and Location
   Mohsen Saffari, Mahdi Khodayar, Mohammad E. Khodayar, Seyed Saeed Fazlhashemi · 2025 · IEEE Transactions on Artificial Intelligence
3. Intelligent multi-sensor fusion and anomaly detection in vehicles via deep learning
   Murat Arda Önsü, Murat Şimşek, Mark Fobert, Burak Kantarcı · 2025 · Internet of Things
4. Semantic segmentation with deep learning: detection of cracks at the cut edge of glass
   Michael Drass, Hagen Berthold, Michael Anton Kraus, Steffen Müller-Braun · 2020 · Glass Structures & Engineering
5. Variational autoencoder based receiver for orthogonal time frequency space modulation
   Qiao Li, Zheng Xiang, Peng Ren, Wanlu Li · 2021 · Digital Signal Processing
6. Deconvolutional Density Network: Modeling Free-Form Conditional Distributions
   Bing Chen, Mazharul Islam, Jisuo Gao, Lin Wang · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
7. Structured Variational Bayesian Inference for Gaussian State-Space Models With Regime Switching
   Yohan Petetin, Yazid Janati, François Desbouvries · 2021 · IEEE Signal Processing Letters
8. MUGL: Large Scale Multi Person Conditional Action Generation with Locomotion
   Shubh Maheshwari, Debtanu Gupta, Ravi Kiran Sarvadevabhatla · 2022 · IEEE Winter Conference on Applications of Computer Vision
9. Generalized Probabilistic U-Net for Medical Image Segementation
   Ishaan Bhat, Josien P. W. Pluim, Hugo J. Kuijf · 2022 · Lecture notes in computer science
10. Association between prenatal alcohol exposure and children's facial shape: a prospective population-based cohort study
    Xianjing Liu, Manfred Kayser, Steven A. Kushner, Henning W. Tiemeier, Fernando Rivadeneira, Vincent W. V. Jaddoe, Wiro J. Niessen, Eppo Bonne Wolvius, Gennady V. Roshchupkin · 2023 · Human Reproduction
11. Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?
    Pedro Lencastre, Marit Gjersdal, Leonardo Rydin Gorjão, Anis Yazidi, Pedro G. Lind · 2023 · Physica D Nonlinear Phenomena
12. Generative modelling of vibration signals in machine maintenance
    Andrzej Puchalski, Iwona Komorska · 2023 · Eksploatacja i Niezawodnosc - Maintenance and Reliability
13. Unpaired Downscaling of Fluid Flows with Diffusion Bridges
    Tobias Bischoff, Katherine M. Deck · 2024 · Artificial Intelligence for the Earth Systems
14. Generative models of T-cell receptor sequences
    Giulio Isacchini, Zachary M. Sethna, Yuval Elhanati, Armita Nourmohammad, Aleksandra M. Walczak, Thierry Mora · 2020 · Physical review. E
15. Ship Detection in SAR Images Using Convolutional Variational Autoencoders
    Nuno Ferreira, Margarida Silveira · 2020 · IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
16. Data‐driven inference of interactions among multiple tourist attractions for hourly demand forecasting
    Rong Zhao, Feilong Wang, Weimin Zheng · 2022 · International Journal of Tourism Research
17. Introducing µGUIDE for quantitative imaging via generalized uncertainty-driven inference using deep learning
    Maëliss Jallais, Marco Palombo · 2024 · eLife
18. Classification and reconstruction of optical quantum states with deep neural networks
    Shahnawaz Ahmed, Carlos Sánchez Muñoz, Franco Nori, Anton Frisk Kockum · 2021 · Physical Review Research
19. Application of latent variable models for hidden pattern identification and machine learning prediction improvement in structural engineering
    Sergei Shturmin, Sujith Mangalathu, Jong‐Su Jeon · 2025 · Engineering Applications of Artificial Intelligence
20. Diffusion-Based Surrogate Modeling and Multi-Fidelity Calibration
    Naichen Shi, Hao Yan, Shenghan Guo, Raed Al Kontar · 2025 · IEEE Transactions on Automation Science and Engineering
21. Enhanced 3D tumor synthesis and segmentation framework using multiscale diffusion and hybrid SAM-Swin models across diverse anatomical datasets
    Jincao Yao, Mudassar Ali, Wenjie Zheng, Jiaqi Hu, Jing Wang, Xingze Zou, Haoji Roland Hu, Qiong Luo, Weizeng Zheng, Neng Jin et al. · 2025 · Neurocomputing
22. Cybersecurity Alert Prioritization in a Critical High Power Grid With Latent Spaces
    Juan Ramón Feijoo-Martínez, Alicia Guerrero-Curieses, Francisco-Javier Gimeno-Blanes, Mario Castro-Fernández, José Luis Rojo‐Álvarez · 2023 · IEEE Access
23. Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation
    Hyojoon Park, Bin Li, Yuming Liu, Michael S. Nelson, Helen M. Wilson, Eftychios D. Sifakis, Kevin W. Eliceiri · 2023 · Medical Image Analysis
24. ML Pro: digital assistance system for interactive machine learning in production
    Christian Neunzig, Dennis Möllensiep, Bernd Kuhlenkötter, Matthias Möller · 2023 · Journal of Intelligent Manufacturing
25. Probabilistic Brain Extraction in MR Images via Conditional Generative Adversarial Networks
    Saeed Moazami, Deep Ray, Daniel Pelletier, Assad A. Oberai · 2023 · IEEE Transactions on Medical Imaging
26. Cocreative Interaction: Somax2 and the REACH Project
    Gérard Assayag, Laurent Bonnasse‐Gahot, Joakim Borg · 2022 · Computer Music Journal
27. Predicting Rock Burst in Underground Engineering Leveraging a Novel Metaheuristic-Based LightGBM Model
    Kai Wang, Biao He, Pijush Samui, Jian Zhou · 2024 · Computer Modeling in Engineering & Sciences
28. Deep variational magnetic resonance image denoising via network conditioning
    Hazique Aetesam, Suman Kumar Maji · 2024 · Biomedical Signal Processing and Control
29. Personalizing Communication and Segmentation with Random Forest Node Embedding
    Weiwei Wang, Wiebke Eberhardt, Stefano Bromuri · 2024 · Expert Systems with Applications
30. APM: Adaptive parameter multiplexing for class incremental learning
    Jinghan Gao, Tao Xie, Ruifeng Li, Ke Wang, Li-Jun Zhao · 2024 · Expert Systems with Applications
31. Generation of molecular conformations using generative adversarial neural networks
    Congsheng Xu, Xiaomei Deng, Yi Nan Lu, Peiyuan Yu · 2024 · Digital Discovery
32. Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
    Farhad Pourkamali‐Anaraki, Jamal F. Husseini, Scott Edward Stapleton · 2024 · IEEE Access
33. VAE-CNN: Deep Learning on Small Sample Dataset Improves Hydrogen Yield Prediction in Co-gasification
    Thavavel Vaiyapuri, Walaa Hassan Elashmawi, S. Shridevi, William Asiedu · 2024 · Journal of Computational and Cognitive Engineering
34. Unsupervised data imputation with multiple importance sampling variational autoencoders
    Shenfen Kuang, Yewen Huang, Jie Song · 2025 · Scientific Reports
35. An Interpretable and Domain-Informed Real-Time Hybrid Earthquake Early Warning for Ground Shaking Intensity Prediction
    Jawad Fayaz, Rodrigo Astroza, Sergio Ruiz · 2025 · Engineering
36. MF-CGAN: Multifeature Conditional GAN for Synthetic Data Generation in Internet of Medical Things
    Chandrasen Pandey, Vaibhav Tiwari, Sharmila Anand John Francis, Vipin Pal, Diptendu Sinha Roy · 2025 · IEEE Internet of Things Journal
37. Adversarial regularized diffusion model for fair recommendations
    Ran Yang, Yihao Zhang, Kaibei Li, Qinyang He, Xiaokang Li, Wei Guo Zhou · 2025 · Neural Networks
38. Density based semi-automatic labeling on multi-feature representations for ground truth generation: Application to handwritten character recognition
    Papangkorn Inkeaw, Piyachat Udomwong, Jeerayut Chaijaruwanich · 2021 · Knowledge-Based Systems
39. Content Based COVID-19 Chest X-Ray and CT Images Retrieval framework using Stacked Auto-Encoders
    Fatima Zahra Benyelles, Amel Sekkal, Nesma Settouti · 2021 · International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)
40. Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *
    Maxim A Ziatdinov, Chun Yin Wong, Sergei V. Kalinin · 2023 · Machine Learning Science and Technology
41. Spatial point processes and neural networks: A convenient couple
    Jorge Mateu, Abdollah Jalilian · 2022 · Spatial Statistics
42. Machine learning in scanning transmission electron microscopy
    2022 · Nature Reviews Methods Primers
43. Machine Learning for Antimicrobial Resistance Research and Drug Development
    Shamanth Adekhandi Shankarnarayan, Joshua D. Guthrie, Daniel A. Charlebois · 2022 · IntechOpen eBooks
44. Investigation of in-liquid ordering mediated transformations in Al-Sc via ab initio molecular dynamics and unsupervised learning
    Deep Choudhuri, Bhaskar S. Majumdar, Hunter Wilkinson · 2022 · Physical Review Materials
45. Computational protein design with data‐driven approaches: Recent developments and perspectives
    Haiyan Liu, Quan Chen · 2022 · Wiley Interdisciplinary Reviews Computational Molecular Science
46. Detection of abnormal extraocular muscles in small datasets of computed tomography images using a three-dimensional variational autoencoder
    Yeon Woong Chung, In Young Choi · 2023 · Scientific Reports
47. Creating Synthetic Volatility Surfaces using Generative Adversarial Networks with Static Arbitrage Loss Conditions
    Thendo Sidogi, Wilson Tsakane Mongwe, Rendani Mbuvha, Tshilidzi Marwala · 2022 · IEEE Symposium Series on Computational Intelligence (SSCI)
48. Compression and reconstruction of flotation foam images based on generative adversarial networks
    Runda Jia, Yi Yan, Du Lang, Dakuo He, Kang Li · 2023 · Minerals Engineering
49. Feature-based magnetotelluric inversion by variational autoencoder using a subdomain encoding scheme
    Hongyu Zhou, Rui Guo, Maokun Li, Fan Yang, Shenheng Xu, Aria Abubakar · 2023 · Geophysics
50. Discriminating Known from Unknown Objects via Structure-Enhanced Recurrent Variational AutoEncoder
    Aming Wu, Cheng Dan Deng · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
51. Deep Unsupervised Representation Learning for Feature-Informed EEG Domain Extraction
    Han Wei Ng, Cuntai Guan · 2023 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
52. Generative Modeling of Residuals for Real-Time Risk-Sensitive Safety with Discrete-Time Control Barrier Functions
    Ryan K. Cosner, Igor Sadalski, Jana K. Woo, Preston Culbertson, Aaron D. Ames · 2024 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
53. Split Learning Without Local Weight Sharing to Enhance Client-Side Data Privacy
    Ngoc Duy Pham, Khoa T. Phan, Alsharif Abuadbba, Yansong Gao, Van-Doan Nguyen, Naveen Chilamkurti · 2025 · IEEE Transactions on Dependable and Secure Computing
54. Deep Learning for the Analysis of Disruption Precursors Based on Plasma Tomography
    Diogo R. Ferreira, Pedro J. Carvalho, Carlo Sozzi, P. Lomas, Jet Contributors · 2020 · Fusion Science & Technology
55. Aerial Imagery Feature Engineering Using Bidirectional Generative Adversarial Networks: A Case Study of the Pilica River Region, Poland
    Maciej Adamiak, Krzysztof Marek Będkowski, Anna Majchrowska · 2021 · Remote Sensing
56. Simulating real profiles for shilling attacks: A generative approach
    Julio Barbieri, Leandro G.M. Alvim, Filipe Braida, Geraldo Zimbrão · 2021 · Knowledge-Based Systems
57. B1 field map synthesis with generative deep learning used in the design of parallel-transmit RF pulses for ultra-high field MRI
    Boris Eberhardt, Benedikt Andreas Poser, Nadim Jon Shah, Jörg Felder · 2022 · Zeitschrift für Medizinische Physik
58. Real-time anomaly detection in seasonal time series with conditional variational autoencoder
    Lorenzo Porcelli, Marcello Trovati, Francesco Palmieri · 2025 · Applied Soft Computing
59. AΙ-Driven Drug Repurposing: Applications and Challenges
    Paraskevi Keramida, Nikolaos Konstantinos Syrigos, Marousa Kouvela, Garyphallia Poulakou, Andriani G. Charpidou, Oraianthi Fiste · 2025 · Medicines
60. Generative Artificial Intelligence: Applications and Future Prospects in Dentistry
    Zhiyuan Ma, Chenlin Du, Qicheng Lao, Xianju Xie · 2025 · International Dental Journal
61. DeepLTRS: A deep latent recommender system based on user ratings and reviews
    Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche · 2021 · Pattern Recognition Letters
62. Blind source separation by long-term monitoring: A variational autoencoder to validate the clustering analysis
    Domenico DE SALVIO, Michael J. Bianco, Peter Gerstoft, Dario D’Orazio, Massimo Garai · 2023 · The Journal of the Acoustical Society of America
63. Time-Resolved Line Shapes of Single Quantum Emitters via Machine Learned Photon Correlations
    Andrew H. Proppe, Kin Long Kelvin Lee, Alexander E. K. Kaplan, Matthias Ginterseder, Chantalle J. Krajewska, Moungi G. Bawendi · 2023 · Physical Review Letters
64. Combining variational autoencoders and physical bias for improved microscopy data analysis ∗
    Arpan Biswas, Maxim A Ziatdinov, Sergei V. Kalinin · 2023 · Machine Learning Science and Technology
65. A scalable crystal representation for reverse engineering of novel inorganic materials using deep generative models
    Rochan Bajpai, Atharva Shukla, Janish Kumar, Abhishek Tewari · 2023 · Computational Materials Science
66. Generalizing Across Domains in Diabetic Retinopathy via Variational Autoencoders
    Sharon Chokuwa, Muhammad Haris Khan · 2023 · Lecture notes in computer science
67. Enhancement of Track Damage Identification by Data Fusion of Vibration-Based Image Representation
    Shaohua Wang, Lihua Tang, Yinling Dou, Zhaoyu Li, Kean Chin Aw · 2023 · Journal of Nondestructive Evaluation
68. A Missing Well-Logs Imputation Method Based on Conditional Denoising Diffusion Probabilistic Models
    Han Meng, Botao Lin, Ruxin Zhang, Yan Jin · 2024 · SPE Journal
69. CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory
    Yao He, Jing Yang, Shaobo Li, Jianjun Hu, Yaping Ren, Qing Ji · 2024 · Complex & Intelligent Systems
70. MagGen: A Graph-Aided Deep Generative Model for Inverse Design of Permanent Magnets
    Sourav Mal, Gaurav Seal, Prasenjit Sen · 2024 · The Journal of Physical Chemistry Letters
71. VAE-LSTM Data Augmentation for Cattle Behavior Classification Using a Wearable Inertial Sensor
    Thai-Ha Dang, Jaehee Park, Thang Viet Tran, Wan‐Young Chung · 2024 · IEEE Sensors Letters
72. Adversarial Attacks on Vision-Language Model-Empowered Chatbots in Consumer Electronics
    Yingjia Shang, Zhijun Liu, Jiawen Kang, M. Shamim Hossain, Yi Wu · 2024 · IEEE Transactions on Consumer Electronics
73. Multiscale simulation of spatially correlated microstructure via a latent space representation
    Reese E. Jones, Craig M. Hamel, Dan Bolintineanu, Kyle L. Johnson, Robert Buarque de Macedo, Jan N. Fuhg, Nikolaos Bouklas, Sharlotte Kramer · 2024 · International Journal of Solids and Structures
74. Parsimonious airfoil Parameterisation: A deep learning framework with Bidirectional LSTM and Gaussian Mixture models
    Vincent le Roux, Marelie Hattingh Davel, Johan Bosman · 2024 · Expert Systems with Applications
75. Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation
    Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyıldız, Mark Girolami · 2024 · Journal of Computational Physics
76. An ensemble method for investigating maritime casualties resulting in pollution occurrence: Data augmentation and feature analysis
    Duowei Li, Yiik Diew Wong, Tianyi Chen, Nanxi Wang, Kum Fai Yuen · 2024 · Reliability Engineering & System Safety
77. Diffusion-Based Graph Generative Methods
    Hongyang Chen, Can Xu, Lingyu Zheng, Qiang Zhang, Xuemin Lin · 2024 · IEEE Transactions on Knowledge and Data Engineering
78. ParaDC: Parallel-learning-based dynamometer cards augmentation with diffusion models in sucker rod pump systems
    Xingxia Wang, Yuhang Liu, Xiang Cheng, Yutong Wang, Yonglin Tian, Fei–Yue Wang · 2024 · Neurocomputing
79. Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy
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80. The Genomic Code: the genome instantiates a generative model of the organism
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81. Quantification of Data Imbalance
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82. ChronoGAN: Supervised and Embedded Generative Adversarial Networks for Time Series Generation
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83. Going digital to boost safe and sustainable materials innovation markets. The digital safe-and-sustainability-by-design innovation approach of the PINK project
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84. Effective Generative Replay with Strong Memory for Continual Learning
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85. A state-of-the-art review of diffusion model applications for microscopic image and micro-alike image analysis
    Yan Liu, Tao Jiang, Rui Li, Lingling Yuan, Marcin Grzegorzek, Chen Li, Xiaoyan Li · 2025 · Frontiers in Medicine
86. Bridging Traditional-Statistics and Machine-Learning Approaches in Psychology: Navigating Small Samples, Measurement Error, Nonindependent Observations, and Missing Data
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87. Explaining 3D Semantic Segmentation Through Generative AI ‐Based Counterfactuals
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88. Diffusion Models and Representation Learning: A Survey
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89. Quantifying Uncertainty in Physics-Informed Variational Autoencoders for Anomaly Detection
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90. Color Conversion in Deep Autoencoders
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91. End-to-end differentiability and tensor processing unit computing to accelerate materials’ inverse design
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92. A Hybrid Capsule Network-based Deep Learning Framework for Deciphering Ancient Scripts with Scarce Annotations: A Case Study on Phoenician Epigraphy
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93. Semi-Supervised Gaussian Mixture Variational Autoencoder for Pulse Shape Discrimination
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94. Spatial voting models in circular spaces: A case study of the U.S. House of Representatives
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95. Training Process of Unsupervised Learning Architecture for Gravity Spy Dataset
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96. A Mathematical Model for Simulation of Vasoplegic Shock and Vasopressor Therapy
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97. Interpreting denoising autoencoders with complex perturbation approach
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98. Learning binary and sparse permutation-invariant representations for fast and memory efficient whole slide image search
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99. Image embedding for denoising generative models
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100. ColDBin: Cold Diffusion for Document Image Binarization
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