Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks

30 October 2019

Papers citing "Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks"

5 / 5 papers shown

Title
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead Won-Jun Jang Hyeon-Seo Park Si-Hyeon Lee FedML 196 0 0 10 Feb 2025
Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation Charles OÑeill Y. Ting 丁 I. Ciucă Jack Miller Thang Bui SyDa 37 1 0 15 Aug 2023
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 59 186 0 17 Feb 2021
Local and non-local dependency learning and emergence of rule-like representations in speech data by Deep Convolutional Generative Adversarial Networks Gašper Beguš GAN 16 13 0 27 Sep 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 297 10,368 0 12 Dec 2018