PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs

26 February 2020

Papers citing "PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs"

8 / 8 papers shown

Title
GDPP: Learning Diverse Generations Using Determinantal Point Process Mohamed Elfeki Camille Couprie M. Rivière Mohamed Elhoseiny 55 64 0 30 Nov 2018
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning Akash Srivastava Lazar Valkov Chris Russell Michael U. Gutmann Charles Sutton SyDa GAN 60 678 0 22 May 2017
Least Squares Generative Adversarial Networks Xudong Mao Qing Li Haoran Xie Raymond Y. K. Lau Zhen Wang Stephen Paul Smolley GAN 305 4,569 0 13 Nov 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling Jiajun Wu Chengkai Zhang Tianfan Xue Bill Freeman J. Tenenbaum GAN 283 1,952 0 24 Oct 2016
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 147 2,921 0 07 Oct 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 454 9,027 0 10 Jun 2016
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 412 16,947 0 20 Dec 2013
Determinantal point processes for machine learning Alex Kulesza B. Taskar 235 1,134 0 25 Jul 2012