VOS: a Method for Variational Oversampling of Imbalanced Data

7 September 2018

Papers citing "VOS: a Method for Variational Oversampling of Imbalanced Data"

8 / 8 papers shown

Title
Variational Autoencoders for Collaborative Filtering Dawen Liang Rahul G. Krishnan Matthew D. Hoffman Tony Jebara BDL 181 1,239 0 16 Feb 2018
Variational Autoencoder for Deep Learning of Images, Labels and Captions Yunchen Pu Zhe Gan Ricardo Henao Xin Yuan Chunyuan Li Andrew Stevens Lawrence Carin BDL CoGe 86 753 0 28 Sep 2016
Understanding data augmentation for classification: when to warp? S. Wong Adam Gatt V. Stamatescu Mark D Mcdonnell 80 905 0 28 Sep 2016
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 223 633 0 03 Nov 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 268 1,245 0 01 Sep 2015
Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder Xi Zhang Yanwei Fu Andi Zang Leonid Sigal G. Agam SyDa 46 38 0 11 Mar 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,929 0 20 Dec 2013
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 371 25,646 0 09 Jun 2011