{"total":83,"rows":[{"id":"2206.07579","title":"A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions","created":"2022-06-15","cited_by_count":73,"area":null},{"id":"2106.07873","title":"Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images","created":"2021-06-15","cited_by_count":58,"area":null},{"id":"2501.00895","title":"Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model","created":"2025-01-01","cited_by_count":48,"area":null},{"id":"2206.03066","title":"Recent Advances for Quantum Neural Networks in Generative Learning","created":"2022-06-07","cited_by_count":39,"area":null},{"id":"2202.07145","title":"GAN-generated Faces Detection: A Survey and New Perspectives","created":"2022-02-15","cited_by_count":30,"area":null},{"id":"2203.01593","title":"3D Human Motion Prediction: A Survey","created":"2022-03-03","cited_by_count":30,"area":null},{"id":"2305.17473","title":"A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRU","created":"2023-05-27","cited_by_count":25,"area":null},{"id":"2201.07646","title":"A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis","created":"2022-01-19","cited_by_count":24,"area":null},{"id":"2204.08329","title":"A Comprehensive Survey on Data-Efficient GANs in Image Generation","created":"2022-04-18","cited_by_count":20,"area":null},{"id":"2307.14397","title":"A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot","created":"2023-07-26","cited_by_count":19,"area":null},{"id":"2210.05461","title":"FreGAN: Exploiting Frequency Components for Training GANs under Limited Data","created":"2022-10-11","cited_by_count":16,"area":null},{"id":"2110.12076","title":"Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Review","created":"2021-10-22","cited_by_count":15,"area":null},{"id":"2210.08216","title":"UDoc-GAN: Unpaired Document Illumination Correction with Background Light Prior","created":"2022-10-15","cited_by_count":15,"area":null},{"id":"2312.00739","title":"Adversarial Score Distillation: When score distillation meets GAN","created":"2023-12-01","cited_by_count":15,"area":null},{"id":"2503.04641","title":"Simulating the Real World: A Unified Survey of Multimodal Generative Models","created":"2025-03-06","cited_by_count":15,"area":null},{"id":"2107.05680","title":"Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions","created":"2021-07-12","cited_by_count":14,"area":null},{"id":"2308.16316","title":"Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art","created":"2023-08-30","cited_by_count":14,"area":null},{"id":"2402.18062","title":"Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities","created":"2024-02-28","cited_by_count":14,"area":null},{"id":"2302.01075","title":"MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows","created":"2023-02-02","cited_by_count":13,"area":null},{"id":"2302.08641","title":"Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Survey","created":"2023-02-17","cited_by_count":10,"area":null},{"id":"2306.17170","title":"An Overview on Generative AI at Scale with Edge-Cloud Computing","created":"2023-06-02","cited_by_count":9,"area":null},{"id":"2307.16879","title":"Image Synthesis under Limited Data: A Survey and Taxonomy","created":"2023-07-31","cited_by_count":9,"area":null},{"id":"2405.19684","title":"A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning","created":"2024-05-30","cited_by_count":9,"area":null},{"id":"2405.20024","title":"Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey","created":"2024-05-30","cited_by_count":9,"area":null},{"id":"2407.15500","title":"TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping","created":"2024-07-22","cited_by_count":9,"area":null},{"id":"2502.04573","title":"Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer","created":"2025-02-06","cited_by_count":8,"area":null},{"id":"2106.06976","title":"Game of GANs: Game-Theoretical Models for Generative Adversarial Networks","created":"2021-06-13","cited_by_count":6,"area":null},{"id":"2211.08179","title":"Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions","created":"2022-11-15","cited_by_count":6,"area":null},{"id":"2309.15995","title":"Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems","created":"2023-09-27","cited_by_count":6,"area":null},{"id":"2404.03354","title":"A Comprehensive Survey on Self-Supervised Learning for Recommendation","created":"2024-04-04","cited_by_count":6,"area":null},{"id":"2302.06223","title":"Variational Mixture of HyperGenerators for Learning Distributions Over Functions","created":"2023-02-13","cited_by_count":5,"area":null},{"id":"2303.17192","title":"Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments","created":"2023-03-30","cited_by_count":5,"area":null},{"id":"2506.03216","title":"A Survey of Deep Learning Video Super-Resolution","created":"2025-06-03","cited_by_count":5,"area":null},{"id":"2102.04699","title":"Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared Discriminator","created":"2021-02-09","cited_by_count":4,"area":null},{"id":"2107.14776","title":"Synthetic flow-based cryptomining attack generation through Generative Adversarial Networks","created":"2021-07-30","cited_by_count":4,"area":null},{"id":"2207.01750","title":"Federated Split GANs","created":"2022-07-04","cited_by_count":4,"area":null},{"id":"2210.06334","title":"A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis","created":"2022-10-09","cited_by_count":4,"area":null},{"id":"2111.10722","title":"A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel","created":"2021-11-21","cited_by_count":3,"area":null},{"id":"2205.10179","title":"Towards the Generation of Synthetic Images of Palm Vein Patterns: A Review","created":"2022-05-20","cited_by_count":3,"area":null},{"id":"2310.10958","title":"Enhancing Deep Neural Network Training Efficiency and Performance through Linear Prediction","created":"2023-10-17","cited_by_count":3,"area":null},{"id":"2310.14556","title":"S3Aug: Segmentation, Sampling, and Shift for Action Recognition","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2401.13555","title":"Benchmarking the Fairness of Image Upsampling Methods","created":"2024-01-24","cited_by_count":3,"area":null},{"id":"2407.12200","title":"This Probably Looks Exactly Like That: An Invertible Prototypical Network","created":"2024-07-16","cited_by_count":3,"area":null},{"id":"2201.03353","title":"GMFIM: A Generative Mask-guided Facial Image Manipulation Model for Privacy Preservation","created":"2022-01-10","cited_by_count":2,"area":null},{"id":"2204.10495","title":"Adversarial Estimators","created":"2022-04-22","cited_by_count":2,"area":null},{"id":"2403.14340","title":"Exploring Task Unification in Graph Representation Learning via Generative Approach","created":"2024-03-21","cited_by_count":2,"area":null},{"id":"2406.03117","title":"VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by Regularizing Unwanted Noise","created":"2024-06-05","cited_by_count":2,"area":null},{"id":"2504.04271","title":"ADA-Net: Attention-Guided Domain Adaptation Network with Contrastive Learning for Standing Dead Tree Segmentation Using Aerial Imagery","created":"2025-04-05","cited_by_count":2,"area":null},{"id":"2508.20670","title":"\"Humor, Art, or Misinformation?\": A Multimodal Dataset for Intent-Aware Synthetic Image Detection","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2510.14075","title":"DiffOPF: Diffusion Solver for Optimal Power Flow","created":"2025-10-15","cited_by_count":2,"area":null},{"id":"2101.11600","title":"Synthetic Generation of Three-Dimensional Cancer Cell Models from Histopathological Images","created":"2021-01-26","cited_by_count":1,"area":null},{"id":"2108.07975","title":"Unsupervised Image Generation with Infinite Generative Adversarial Networks","created":"2021-08-18","cited_by_count":1,"area":null},{"id":"2110.05478","title":"An In-depth Summary of Recent Artificial Intelligence Applications in Drug Design","created":"2021-10-10","cited_by_count":1,"area":null},{"id":"2110.15914","title":"Improving the quality of generative models through Smirnov transformation","created":"2021-10-29","cited_by_count":1,"area":null},{"id":"2112.12263","title":"Crash Data Augmentation Using Conditional Generative Adversarial Networks (CGAN) for Improving Safety Performance Functions","created":"2021-12-21","cited_by_count":1,"area":null},{"id":"2203.11410","title":"Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue","created":"2022-03-22","cited_by_count":1,"area":null},{"id":"2205.03947","title":"High-Resolution UAV Image Generation for Sorghum Panicle Detection","created":"2022-05-08","cited_by_count":1,"area":null},{"id":"2206.06444","title":"A method for comparing multiple imputation techniques: a case study on the U.S. National COVID Cohort Collaborative","created":"2022-06-13","cited_by_count":1,"area":null},{"id":"2208.10413","title":"On Deep Learning in Password Guessing, a Survey","created":"2022-08-22","cited_by_count":1,"area":null},{"id":"2301.08830","title":"ApproxED: Approximate exploitability descent via learned best responses","created":"2023-01-20","cited_by_count":1,"area":null},{"id":"2301.10173","title":"Accurate Detection of Paroxysmal Atrial Fibrillation with Certified-GAN and Neural Architecture Search","created":"2023-01-17","cited_by_count":1,"area":null},{"id":"2304.03932","title":"3D GANs and Latent Space: A comprehensive survey","created":"2023-04-08","cited_by_count":1,"area":null},{"id":"2306.16951","title":"Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula","created":"2023-06-01","cited_by_count":1,"area":null},{"id":"2404.06946","title":"A Survey on the Integration of Generative AI for Critical Thinking in Mobile Networks","created":"2024-04-10","cited_by_count":1,"area":null},{"id":"2410.12814","title":"Leveraging generative models to characterize the failure conditions of image classifiers","created":"2024-10-01","cited_by_count":1,"area":null},{"id":"2502.16535","title":"Rebalancing the Scales: A Systematic Mapping Study of Generative Adversarial Networks (GANs) in Addressing Data Imbalance","created":"2025-02-23","cited_by_count":1,"area":null},{"id":"2509.20411","title":"Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation","created":"2025-09-24","cited_by_count":1,"area":null},{"id":"2205.14751","title":"A Generative Adversarial Network-based Selective Ensemble Characteristic-to-Expression Synthesis (SE-CTES) Approach and Its Applications in Healthcare","created":"2022-05-29","cited_by_count":0,"area":null},{"id":"2208.11782","title":"Maximum Likelihood on the Joint (Data, Condition) Distribution for Solving Ill-Posed Problems with Conditional Flow Models","created":"2022-08-24","cited_by_count":0,"area":null},{"id":"2209.00617","title":"Fair mapping","created":"2022-09-01","cited_by_count":0,"area":null},{"id":"2211.10418","title":"Sample-efficient Quantum Born Machine through Coding Rate Reduction","created":"2022-11-14","cited_by_count":0,"area":null},{"id":"2211.14667","title":"Deep Fake Detection, Deterrence and Response: Challenges and Opportunities","created":"2022-11-26","cited_by_count":0,"area":null},{"id":"2302.04099","title":"Extragradient-Type Methods with $\\mathcal{O} (1/k)$ Last-Iterate Convergence Rates for Co-Hypomonotone Inclusions","created":"2023-02-08","cited_by_count":0,"area":null},{"id":"2305.00510","title":"Towards AI-Architecture Liberty: A Comprehensive Survey on Design and Generation of Virtual Architecture by Deep Learning","created":"2023-04-30","cited_by_count":0,"area":null},{"id":"2309.02614","title":"Utilizing Generative Adversarial Networks for Stable Structure Generation in Angry Birds","created":"2023-09-05","cited_by_count":0,"area":null},{"id":"2405.19277","title":"Deep Latent Variable Modeling of Physiological Signals","created":"2024-05-29","cited_by_count":0,"area":null},{"id":"2410.22297","title":"Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization","created":"2024-10-29","cited_by_count":0,"area":null},{"id":"2503.21489","title":"Shape Modeling of Longitudinal Medical Images: From Diffeomorphic Metric Mapping to Deep Learning","created":"2025-03-27","cited_by_count":0,"area":null},{"id":"2504.12352","title":"Deep Generative Model-Based Generation of Synthetic Individual-Specific Brain MRI Segmentations","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2505.20498","title":"ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generation","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2510.26892","title":"BI-DCGAN: A Theoretically Grounded Bayesian Framework for Efficient and Diverse GANs","created":"2025-10-30","cited_by_count":0,"area":null},{"id":"2604.23281","title":"Contrastive Learning for Multimodal Human Activity Recognition with Limited Labeled Data","created":"2026-04-25","cited_by_count":0,"area":null},{"id":"2609.22217","title":"UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}