An Introduction to Variational Autoencoders

Cited by (1,002)

Items 501–600 of 1,002

1. Bi-AAE: A binary adversarial autoencoder deep neural network model for anomaly detection in system-levels marine diesel engines
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2. DDPM-SegFormer: Highly refined feature land use and land cover segmentation with a fused denoising diffusion probabilistic model and transformer
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4. VolGAN: A Generative Model for Arbitrage-Free Implied Volatility Surfaces
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5. Anomaly Detection in Video Data Based on Probabilistic Latent Space Models
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6. A Hybrid Conditional Variational Autoencoder Model for Personalised Top-n Recommendation
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7. Protein A-like Peptide Design Based on Diffusion and ESM2 Models
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8. A semi-supervised approach to dark matter searches in direct detection data with machine learning
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9. Cyber Security Risk management with attack detection frameworks using multi connect variational auto-encoder with probabilistic Bayesian networks
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10. An Introduction to Machine Learning: a perspective from Statistical Physics
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11. Capabilities and limits of autoencoders for extracting collective variables in atomistic materials science
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12. An artificial‐intelligence‐based age‐specific template construction framework for brain structural analysis using magnetic resonance images
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13. Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis
    Paolo Braca, Leonardo Maria Millefiori, Augusto Aubry, Stefano Maranò, Antonio De Maio, Peter Willett · 2022 · IEEE Open Journal of Signal Processing
14. Interpretation for Variational Autoencoder Used to Generate Financial Synthetic Tabular Data
    Jinhong Wu, Konstantinos N. Plataniotis, Lucy Liu, Ehsan Amjadian, Yuri Lawryshyn · 2023 · Algorithms
15. Comparing forward and inverse design paradigms: A case study on refractory high-entropy alloys
    Arindam Debnath, Lavanya Raman, Wenjie Li, Adam M. Krajewski, Marcia Ahn, Shuang Lin, Shun‐Li Shang, Allison M. Beese, Zi‐Kui Liu, Wesley F. Reinhart · 2023 · Journal of materials research/Pratt's guide to venture capital sources
16. Conditional variational autoencoder with Gaussian process regression recognition for parametric models
    Xuehan Zhang, Lijian Jiang · 2023 · Journal of Computational and Applied Mathematics
17. Achieving explainability for plant disease classification with disentangled variational autoencoders
    Harshana Habaragamuwa, Yu Oishi, Kenichi Tanaka · 2024 · Engineering Applications of Artificial Intelligence
18. Predicting drug activity against cancer through genomic profiles and SMILES
    Maryam Abbasi, Filipa G. Carvalho, Bernardete Ribeiro, Joel Perdiz Arrais · 2024 · Artificial Intelligence in Medicine
19. Application of artificial intelligence and machine learning in drug repurposing
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20. Machine Learning to Promote Efficient Screening of Low‐Contact Electrode for 2D Semiconductor Transistor Under Limited Data
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21. Challenges and applications in generative AI for clinical tabular data in physiology
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22. Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization
    Sibghat Ullah, Duc Anh Nguyen, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck · 2020 · IEEE Symposium Series on Computational Intelligence (SSCI)
23. Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis
    M. Girard, Alexander R. Hagen, Ian J. Schwerdt, M. Gaumer, Luther W. McDonald, Nathan O. Hodas, Elizabeth R. Jurrus · 2021 · Journal of Nuclear Materials
24. Unsupervised Doppler Radar Based Activity Recognition for e-Healthcare
    Yordanka Karayaneva, Sara Sharifzadeh, Wenda Li, Yanguo Jing, Bo Tan · 2021 · IEEE Access
25. Spiking Autoencoders With Temporal Coding
    Iulia M. Comșa, Luca Versari, Thomas Fischbacher, Jyrki Alakuijala · 2021 · Frontiers in Neuroscience
26. TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor
    Ruochen Jiao, Xiangguo Liu, Bowen Zheng, Dave Liang, Qi Zhu · 2022 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
27. ctGAN: combined transformation of gene expression and survival data with generative adversarial network
    Jaeyoon Kim, Junhee Seok · 2024 · Briefings in Bioinformatics
28. Robust Hardware Trojan Detection Method by Unsupervised Learning of Electromagnetic Signals
    Daehyeon Lee, Jung­hee Lee, Young-Giu Jung, Janghyuk Kauh, Taigon Song · 2024 · IEEE Transactions on Very Large Scale Integration (VLSI) Systems
29. Deep Learning Models for Biometric Recognition based on Face, Finger vein, Fingerprint, and Iris: A Survey
    Saif Mohanad Kadhim, Johnny Koh Siaw Paw, Yaw Chong Tak, Shahad Thamear Abd Al‐Latief · 2024 · Journal of Smart Internet of Things
30. Uncertainty-Aware Graph Contrastive Fusion Network for multimodal physiological signal emotion recognition
    Guangqiang Li, Ning Chen, Hongqing Zhu, Jing Li, Zhangyong Xu, Zhiying Zhu · 2025 · Neural Networks
31. Application of generative artificial intelligence in the aquacultural sector
    Chiara Fini, Simone Gaetano Amato, Daniela Scutaru, Sara Biancardi, F. Antonucci, Simona Violino, L. Ortenzi, E. N. Nemmi, Alessandro Mei, F. Pallottino et al. · 2025 · Aquacultural Engineering
32. Predicting the hardness of diamond-like carbon coatings using machine learning and generative adversarial networks
    Tahir A. Mahmood, Abdul Wasy Zia · 2025 · Journal of Manufacturing Processes
33. Transforming microfluidics for single-cell analysis with robotics and artificial intelligence
    Jinxiong Cheng, Rajiv Anne, Yu‐Chih Chen · 2025 · Lab on a Chip
34. Data-driven image restoration with option-driven learning for big and small astronomical image data sets
    Peng Jia, Runyu Ning, Ruiqi Sun, Xiaoshan Yang, Dongmei Cai · 2020 · Monthly Notices of the Royal Astronomical Society
35. Learning A Continuous and Reconstructible Latent Space for Hardware Accelerator Design
    Qijing Huang, Charles Hong, John Wawrzynek, Mahesh M. Subedar, Yakun Sophia Shao · 2022 · IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
36. KilonovaNet : Surrogate models of kilonova spectra with conditional variational autoencoders
    Kamilė Lukošiūtė, G. Raaijmakers, Z. Doctor, M. Soares-Santos, B. Nord · 2022 · Monthly Notices of the Royal Astronomical Society
37. Image Augmentation based on Variational Autoencoder for Breast Tumor Segmentation
    K. Balaji · 2023 · Academic Radiology
38. Latent indicators for temporal-preserving latent variable models in vibration-based condition monitoring under non-stationary conditions
    Ryan Balshaw, Philippus Stephan Heyns, Daniel Nicolas Wilke, Stephan Schmidt · 2023 · Mechanical Systems and Signal Processing
39. A Semisupervised Deep Hybrid Multitask Model for RUL Prediction
    Yan‐Hui Lin, Lu-Xin Guan, Liang Chang, Enrico Zio · 2023 · IEEE Transactions on Instrumentation and Measurement
40. Molecular generation strategy and optimization based on A2C reinforcement learning in de novo drug design
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41. Advancing Precision Medicine: VAE Enhanced Predictions of Pancreatic Cancer Patient Survival in Local Hospital
    Yuan Wang, Chenbi Li, Zeheng Wang · 2024 · IEEE Access
42. Adapted generative latent diffusion models for accurate pathological analysis in chest X-ray images
    Daniel Iglesias, Joaquim de Moura, Jorge Novo, Marcos Ortega · 2024 · Medical & Biological Engineering & Computing
43. Diabetic retinopathy detection through generative AI techniques: A review
    Vipin Kumar Bansal, Amit Jain, Navpreet Kaur Walia · 2024 · Results in Optics
44. Generative Artificial Intelligence: Enhancing Patient Education in Cardiovascular Imaging
    Ahmed Marey, Abdelrahman M. Saad, Benjamin D. Killeen, Catalina Gómez, Mariia Tregubova, Mathias Unberath, Muhammad Umair · 2023 · BJR|Open
45. Diffusion Model With Gradient Descent Module Guiding Reconstruction for Single-Pixel Imaging
    Chen Huang, Qiurong Yan, Jinwei Yan, Yi Li, Xiaolong Luo, Hui Wang · 2024 · IEEE photonics journal
46. RodinHD: High-Fidelity 3D Avatar Generation with Diffusion Models
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47. LULC-SegNet: Enhancing Land Use and Land Cover Semantic Segmentation with Denoising Diffusion Feature Fusion
    Zongwen Shi, Junfu Fan, Yujie Du, Yuke Zhou, Yi Zhang · 2024 · Remote Sensing
48. Quantifying The Generative Capabilities Of Variational Autoencoders For 3D Car Point Clouds
    Sneha Saha, Stefan Menzel, Leandro Lei Minku, Xin Yao, Bernhard Sendhoff, Patricia Wollstadt · 2020 · IEEE Symposium Series on Computational Intelligence (SSCI)
49. A machine learning model pipeline for detecting wet pavement condition from live scenes of traffic cameras
    Clint Morris, Jidong J. Yang · 2021 · Machine Learning with Applications
50. Deep Learning Applications in Single-Cell Omics Data Analysis
    Nafiseh Erfanian, A. Ali Heydari, Pablo Iáñez Picazo, Afshin Derakhshani, Mohammad GhasemiGol, Mohsen Farahpour, Saeed Nasseri, Hossein Safarpour, Amirhossein Sahebkar · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
51. Generative Adversarial Networks for Dynamic Malware Behavior: A Comprehensive Review, Categorization, and Analysis
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52. Advancing animal farming with deep learning: A systematic review
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53. Computational Intelligence in Stochastic Reconstruction of Porous Microstructures for Image-Based Poro/Micro-Mechanical Modeling
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54. FuXi-ENS: A machine learning model for efficient and accurate ensemble weather prediction
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55. Dexterous Manipulation Through Imitation Learning: A Survey
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56. Machine Learning-Assisted Discovery of Hidden States in Expanded Free Energy Space
    Rangsiman Ketkaew, Fabrizio Creazzo, Sandra Luber · 2022 · The Journal of Physical Chemistry Letters
57. Feature-blind fairness in collaborative filtering recommender systems
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58. A Kalman Variational Autoencoder Model Assisted by Odometric Clustering for Video Frame Prediction and Anomaly Detection
    Giulia Slavic, Abrham Shiferaw Alemaw, Lucio Marcenaro, David Martín, Carlo S. Regazzoni · 2022 · IEEE Transactions on Image Processing
59. Data imputation in IoT using Spatio-Temporal Variational Auto-Encoder
    Shuo Zhang, Jinyi Chen, Jiayuan Chen, Xiaofei Chen, Hejiao Huang · 2023 · Neurocomputing
60. Interpretation of Hyperspectral Shortwave Infrared Core Scanning Data Using SEM-Based Automated Mineralogy: A Machine Learning Approach
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61. Enhancing IoT-Botnet Detection using Variational Auto-encoder and Cost-Sensitive Learning: A Deep Learning Approach for Imbalanced Datasets
    Hassan Wasswa, Timothy Lynar, Hussein A. Abbass · 2023 · IEEE Region 10 Symposium (TENSYMP)
62. 21-cm signal from the Epoch of Reionization: a machine learning upgrade to foreground removal with Gaussian process regression
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63. Fake it till you make it: Synthetic data for emerging carsharing programs
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64. Inverse design of electromagnetic metamaterials: from iterative to deep learning-based methods
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65. Generative vs. Non-Generative AI: Analyzing the Effects of AI on the Architectural Design Process
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66. A Statistical Characterization of Wireless Channels Conditioned on Side Information
    Benedikt Böck, Michael Baur, Nurettin Turan, Dominik Semmler, Wolfgang Utschick · 2024 · IEEE Wireless Communications Letters
67. Sound-Based Unsupervised Fault Diagnosis of Industrial Equipment Considering Environmental Noise
    Jeong-Geun Lee, Kwang Sik Kim, Jang-Hyun Lee · 2024 · Sensors
68. Sparse Non-Linear Vector Autoregressive Networks for Multivariate Time Series Anomaly Detection
    Mohammed Ayalew Belay, Adil Rasheed, Pierluigi Salvo Rossi · 2024 · IEEE Signal Processing Letters
69. A Comprehensive Study of Deep Neural Networks for Unsupervised Deep Learning
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70. A generative model of galactic dust emission using variational autoencoders
    B. Thorne, L. Knox, K. Prabhu · 2021 · Monthly Notices of the Royal Astronomical Society
71. A semi-supervised autoencoder framework for joint generation and classification of breathing
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72. Learning Urban Driving Policies using Deep Reinforcement Learning
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73. Augmenting perception: How artificial intelligence transforms sensory substitution
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74. Realistic galaxy images and improved robustness in machine learning tasks from generative modelling
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75. Deep generative model for therapeutic targets using transcriptomic disease-associated data—USP7 case study
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76. Estimating three- and four-parameter MIRT models with importance-weighted sampling enhanced variational auto-encoder
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77. Learning Representation for Anomaly Detection of Vehicle Trajectories
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78. Robotic Grasp Detection By Learning Representation in a Vector Quantized Manifold
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79. Exploring Designers’ Perceptions and Practices of Collaborating with Generative AI as a Co-creative Agent in a Multi-stakeholder Design Process: Take the Domain of Avatar Design as an Example
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80. Novel method of performance-optimized metastructure design for electromagnetic wave absorption in specific band using deep learning
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81. Integrating Phase Field Modeling and Machine Learning to Develop Process-Microstructure Relationships in Laser Powder Bed Fusion of IN718
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82. Unsupervised Learning of Intrinsic Semantics With Diffusion Model for Person Re-Identification
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83. FairDiffusion: Enhancing equity in latent diffusion models via fair Bayesian perturbation
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84. Surveying Technology Fusion in IoT Networks for IDS: Exploring Datasets, Tools, Challenges, and Research Prospects
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85. Target-specific de novo design of drug candidate molecules with graph-transformer-based generative adversarial networks
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86. Generative AI in the screen and live performance industries: A conceptual framework and prospects for future research
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87. Generative artificial intelligence for Bayesian model updating in digital twins: a review and tutorial
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88. SIDISH integrates single-cell and bulk transcriptomics to identify high-risk cells and guide precision therapeutics through in silico perturbation
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89. Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancement
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90. Land Cover Classification With Gaussian Processes Using Spatio-Spectro-Temporal Features
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91. Data Augmentation for a Virtual-Sensor-Based Nitrogen and Phosphorus Monitoring
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92. Data-Efficient Deep Generative Model with Discrete Latent Representation for High-Fidelity Digital Materials
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93. Performance Evaluation of a Novel Intrusion Detection System in Next Generation Networks
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94. ReBADD-SE: Multi-objective molecular optimisation using SELFIES fragment and off-policy self-critical sequence training
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95. Deciphering tissue heterogeneity from spatially resolved transcriptomics by the autoencoder-assisted graph convolutional neural network
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96. Synthetic Data Generation Using Combinatorial Testing and Variational Autoencoder
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97. Electromagnetic Field Reconstruction and Source Identification Using Conditional Variational Autoencoder and CNN
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98. Machine Learning Approaches for 3D Motion Synthesis and Musculoskeletal Dynamics Estimation: A Survey
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99. Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
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100. Advances in generative modeling methods and datasets to design novel enzymes for renewable chemicals and fuels
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