An Introduction to Variational Autoencoders

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Items 101–200 of 1,002

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2. GANplifying event samples
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9. Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review
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10. Testing human ability to detect ‘deepfake’ images of human faces
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11. An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination
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12. Multiomics Research: Principles and Challenges in Integrated Analysis
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13. Integration of hyperspectral imaging and autoencoders: Benefits, applications, hyperparameter tunning and challenges
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14. Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning
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15. A Survey on an Emerging Safety Challenge for Autonomous Vehicles: Safety of the Intended Functionality
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16. Machine learning in sustainable ship design and operation: A review
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17. Deep learning for blocking in entity matching
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18. A generative model of memory construction and consolidation
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19. Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm
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20. Generative adversarial networks and diffusion models in material discovery
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21. High-throughput microfluidic systems accelerated by artificial intelligence for biomedical applications
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22. A Survey on Variational Autoencoders in Recommender Systems
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23. Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin
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24. Federated Learning-Empowered AI-Generated Content in Wireless Networks
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25. To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review
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26. Generative networks for precision enthusiasts
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27. Semi-Supervised Deep Dynamic Probabilistic Latent Variable Model for Multimode Process Soft Sensor Application
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28. Deep and statistical learning in biomedical imaging: State of the art in 3D MRI brain tumor segmentation
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29. Generative AI in mobile networks: a survey
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30. Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS
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31. The Markov blanket trick: On the scope of the free energy principle and active inference
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32. A deep neural network framework for real-time on-site estimation of acceleration response spectra of seismic ground motions
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33. Hierarchical Graph Convolutional Networks for Action Quality Assessment
    Kanglei Zhou, Yue Ma, Hubert P. H. Shum, Xiaohui Liang · 2023 · IEEE Transactions on Circuits and Systems for Video Technology
34. Deep Learning Enabled Design of Complex Transmission Matrices for Universal Optical Components
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35. Understanding Event-Generation Networks via Uncertainties
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36. Application of machine learning techniques to the analysis and prediction of drug pharmacokinetics
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37. Decoding the brain: From neural representations to mechanistic models
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38. Forecasting Covid-19 Dynamics in Brazil: A Data Driven Approach
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39. A newcomer’s guide to deep learning for inverse design in nano‐photonics
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40. A Review of Generative Models in Generating Synthetic Attack Data for Cybersecurity
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41. Exploring order parameters and dynamic processes in disordered systems via variational autoencoders
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42. Generative AI and process systems engineering: The next frontier
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43. Collective variable discovery in the age of machine learning: reality, hype and everything in between
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44. Application and Construction of Deep Learning Networks in Medical Imaging
    Maribel Torres-Velázquez, Weijie Chen, Xue Li, Alan B. McMillan · 2020 · IEEE Transactions on Radiation and Plasma Medical Sciences
45. GANplifying event samples
    Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, Benjamin Philip Nachman, Tilman Plehn · 2021 · SciPost Physics
46. iCaps-Dfake: An Integrated Capsule-Based Model for Deepfake Image and Video Detection
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47. Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil
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48. GAN-Based Approaches for Generating Structured Data in the Medical Domain
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49. Status and prospects for drought forecasting: opportunities in artificial intelligence and hybrid physical–statistical forecasting
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50. From Turing to Transformers: A Comprehensive Review and Tutorial on the Evolution and Applications of Generative Transformer Models
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51. Generative deep-learning-embedded asynchronous structured light for three-dimensional imaging
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52. Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states
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53. Arousal as a universal embedding for spatiotemporal brain dynamics
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54. Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning
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55. Data augmentation based on diffusion probabilistic model for remaining useful life estimation of aero-engines
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56. Physics-guided Deep Markov Models for learning nonlinear dynamical systems with uncertainty
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57. Anomaly detection and defense techniques in federated learning: a comprehensive review
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58. Transformers for Molecular Property Prediction: Lessons Learned from the Past Five Years
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59. Variational Autoencoder for Image-Based Augmentation of Eye-Tracking Data
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60. Deep learning based automatic detection algorithm for acute intracranial haemorrhage: a pivotal randomized clinical trial
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61. Generative AI for Semantic Communication: Architecture, Challenges, and Outlook
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62. Machine learning in materials design: Algorithm and application*
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63. An Investigation of the Effectiveness of Deepfake Models and Tools
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64. Text-to-Image Synthesis With Generative Models: Methods, Datasets, Performance Metrics, Challenges, and Future Direction
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65. Multi-omics data integration and analysis pipeline for precision medicine: Systematic review
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66. Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics
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67. Unsupervised deep learning approach for structural anomaly detection using probabilistic features
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68. What is generative in generative artificial intelligence? A design-based perspective
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70. Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions
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71. DCTRGAN: Improving the Precision of Generative Models with Reweighting
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72. Design, material, function, and fabrication of metamaterials
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73. Discop: Provably Secure Steganography in Practice Based on "Distribution Copies"
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74. Machine learning for bridge wind engineering
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75. How to GAN Event Unweighting
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86. Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently
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