GAN Model

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, addressing issues like mode collapse, and enhancing controllability over generated outputs, often through integration with other models like diffusion models or reinforcement learning. Applications span diverse fields, including image generation and editing, drug discovery, and data augmentation for tasks where real data is scarce or expensive to obtain, significantly impacting various scientific domains and practical applications. Recent work also highlights the exploration of alternative training methods to improve efficiency and quality, moving beyond traditional adversarial training.

Papers

July 4, 2023

June 29, 2023

Synthetic Demographic Data Generation for Card Fraud Detection Using GANs
Shuo Wang, Terrence Tricco, Xianta Jiang, Charles Robertson, John Hawkin
Generative Adversarial Network Synthetic Data GAN Model Synthetic Data Generation Credit Card Fraud Detection Demographic Data Synthetic Census

June 27, 2023

Learning from Invalid Data: On Constraint Satisfaction in Generative Models
Giorgio Giannone, Lyle Regenwetter, Akash Srivastava, Dan Gutfreund, Faez Ahmed
LeArning Abstract Generative Model GAN Model Novel Training Constraint Satisfaction Constraint Violation

June 26, 2023

June 24, 2023

Evaluating the Utility of GAN Generated Synthetic Tabular Data for Class Balancing and Low Resource Settings
Nagarjuna Chereddy, Bharath Kumar Bolla
Training Data GAN Model Class Imbalance Task Utility GAN Based Synthetic Tabular Data Class Balancing Class Balancing Technique

June 23, 2023

PP-GAN : Style Transfer from Korean Portraits to ID Photos Using Landmark Extractor with GAN
Jongwook Si, Sungyoung Kim
Generative Adversarial Network GAN Model Style Transfer C Gan Style Representation Landmark Detection Facial Landmark Human Portrait

June 21, 2023

Semi-Implicit Denoising Diffusion Models (SIDDMs)
Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou
Generative Model GAN Model Denoising Diffusion Probabilistic Model Denoising Diffusion Denoising Diffusion Implicit Model

June 15, 2023

PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators
Runmin Cong, Wenyu Yang, Wei Zhang, Chongyi Li, Chun-Le Guo, Qingming Huang, Sam Kwong
Generative Adversarial Network GAN Model Underwater Image Underwater Image Enhancement GAN Architecture Dual Discriminator

June 9, 2023

BioGAN: An unpaired GAN-based image to image translation model for microbiological images
Saber Mirzaee Bafti, Chee Siang Ang, Gianluca Marcelli, Md. Moinul Hossain, Sadiya Maxamhud, Anastasios D. Tsaousis
Generative Adversarial Network GAN Model Unsupervised Image to Image Translation Image Translation Model

June 7, 2023

A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions
Darshan Thaker, Paris Giampouras, René Vidal
Adversarial Attack Practical Algorithm GAN Model GAN Inversion Reverse Engineering Deceptive Diffusion Reliable Deep Learning Progressive GAN

June 6, 2023

Origin-Destination Network Generation via Gravity-Guided GAN
Can Rong, Huandong Wang, Yong Li
GAN Model Physic Informed Machine Learning Origin Destination

June 2, 2023

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing
Shaun McKnight, S. Gareth Pierce, Ehsan Mohseni, Christopher MacKinnon, Charles MacLeod, Tom OHare, Charalampos Loukas
GAN Model Synthetic Data Generation Synthetic Datasets Defect Classification Domain Adaption Scientific Image Composite Material Noise Generation Ultrasonic Non Destructive Testing

June 1, 2023

Conditioning Diffusion Models via Attributes and Semantic Masks for Face Generation
Nico Giambi, Giuseppe Lisanti
Diffusion Model GAN Model Cross Attention Face Generation Semantic Mask Rich Attribute Face Manipulation

May 30, 2023

May 25, 2023

May 23, 2023

Exploring Semantic Variations in GAN Latent Spaces via Matrix Factorization
Andrey Palaev, Rustam A. Lukmanov, Adil Khan
Latent Space GAN Model Image Editing Matrix Factorization High Quality Image Semantic Variation Space GAN

GAN Model

Papers

Disentanglement in a GAN for Unconditional Speech Synthesis

AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation

Synthetic Demographic Data Generation for Card Fraud Detection Using GANs

Learning from Invalid Data: On Constraint Satisfaction in Generative Models

A Simple and Effective Baseline for Attentional Generative Adversarial Networks

Procedural content generation of puzzle games using conditional generative adversarial networks

Evaluating the Utility of GAN Generated Synthetic Tabular Data for Class Balancing and Low Resource Settings

PP-GAN : Style Transfer from Korean Portraits to ID Photos Using Landmark Extractor with GAN

Semi-Implicit Denoising Diffusion Models (SIDDMs)

PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

BioGAN: An unpaired GAN-based image to image translation model for microbiological images

A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions

Origin-Destination Network Generation via Gravity-Guided GAN

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

Conditioning Diffusion Models via Attributes and Semantic Masks for Face Generation

Evaluating the feasibility of using Generative Models to generate Chest X-Ray Data

Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows

Non-adversarial training of Neural SDEs with signature kernel scores

Generative Adversarial Reduced Order Modelling

Exploring Semantic Variations in GAN Latent Spaces via Matrix Factorization