Generative Adversarial Network

Generative Adversarial Networks (GANs) are a class of deep learning models designed to generate new data instances that resemble a training dataset. Current research focuses on improving GAN training stability, enhancing the quality and diversity of generated data, and applying GANs to diverse fields like medical imaging, drug discovery, and time series analysis, often incorporating techniques like contrastive learning and disentangled representation learning to improve model performance and interpretability. The ability of GANs to synthesize realistic data addresses critical limitations in data availability and annotation costs across numerous scientific disciplines and practical applications, leading to advancements in areas ranging from medical diagnosis to robotic control.

Papers

February 1, 2023

Distributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach
Yong Xiao, Rong Xia, Yingyu Li, Guangming Shi, Diep N. Nguyen, Dinh Thai Hoang, Dusit Niyato, Marwan Krunz
Generative Adversarial Network Classification Code Network Traffic Edge Network Federated Self Supervised Learning F GAN

January 31, 2023

January 30, 2023

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji
Generative Adversarial Network GAN Model Adversarial Learning GAN Training Discriminative Reply Linear Layer Approximability Hierarchy

January 27, 2023

Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI
Zhifan Gao, Yifeng Guo, Jiajing Zhang, Tieyong Zeng, Guang Yang
Generative Adversarial Network Magnetic Resonance Imaging High Quality Reconstruction Compressed Sensing MRI

January 23, 2023

January 22, 2023

Face Generation from Textual Features using Conditionally Trained Inputs to Generative Adversarial Networks
Sandeep Shinde, Tejas Pradhan, Aniket Ghorpade, Mihir Tale
Generative Adversarial Network Image Generation Face Generation Generative Network Textual Feature Facial Attribute Rich Input Generative Algorithm

January 21, 2023

Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks
Tehseen Zia, Zeeshan Nisar, Shakeeb Murtaza
Generative Adversarial Network Image Classification Counterfactual Explanation Counterfactual Example Cycle Consistent Generative Adversarial Network Instance Generation

January 20, 2023

Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance
Wardah Ali, Eesha Qureshi, Omama Ahmed Farooqi, Rizwan Ahmed Khan
Generative Adversarial Network Class Imbalance Chest X Ray Image Ventilator Associated Pneumonia Pneumonia Detection ChestX Ray8 Dataset

January 19, 2023

Interpreting CNN Predictions using Conditional Generative Adversarial Networks
R T Akash Guna, Raul Benitez, O K Sikha
Convolutional Neural Network Generative Adversarial Network GAN Model Conditional Generative Adversarial Network

January 18, 2023

January 17, 2023

January 15, 2023

Inpainting borehole images using Generative Adversarial Networks
Rachid Belmeskine, Abed Benaichouche
Generative Adversarial Network GAN Based Wasserstein Generative Adversarial Network Borehole Description

January 13, 2023

January 12, 2023

GH-Feat: Learning Versatile Generative Hierarchical Features from GANs
Yinghao Xu, Yujun Shen, Jiapeng Zhu, Ceyuan Yang, Bolei Zhou
Generative Adversarial Network Generative Learning GAN Generator Hierarchical Generative

Generative Adversarial Network

Papers

Distributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach

GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks

A Bayesian Generative Adversarial Network (GAN) to Generate Synthetic Time-Series Data, Application in Combined Sewer Flow Prediction

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer

Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI

StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis

ECGAN: Self-supervised generative adversarial network for electrocardiography

ViGU: Vision GNN U-Net for Fast MRI

Face Generation from Textual Features using Conditionally Trained Inputs to Generative Adversarial Networks

Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks

Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance

Interpreting CNN Predictions using Conditional Generative Adversarial Networks

Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images

Generative Adversarial Networks to infer velocity components in rotating turbulent flows

EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets

Accurate Detection of Paroxysmal Atrial Fibrillation with Certified-GAN and Neural Architecture Search

Inpainting borehole images using Generative Adversarial Networks

Short-length SSVEP data extension by a novel generative adversarial networks based framework

Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing

GH-Feat: Learning Versatile Generative Hierarchical Features from GANs