Interpolation Consistency Training for Semi-Supervised Learning

9 March 2019

Papers citing "Interpolation Consistency Training for Semi-Supervised Learning"

22 / 322 papers shown

Title
CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarios Wenhao Ding Mengdi Xu Ding Zhao 27 52 0 17 Sep 2019
Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets Yang Li Jianhe Yuan Zhiqun Zhao Hao Sun Zhihai He 8 6 0 04 Sep 2019
Semi-supervised Learning of Fetal Anatomy from Ultrasound Jeremy Tan Anselm Au Qingjie Meng Bernhard Kainz 17 10 0 30 Aug 2019
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning Eric Arazo Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness 16 815 0 08 Aug 2019
Sound source detection, localization and classification using consecutive ensemble of CRNN models Slawomir Kapka M. Lewandowski 11 66 0 02 Aug 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 38 840 0 31 Jul 2019
HODGEPODGE: Sound event detection based on ensemble of semi-supervised learning methods Ziqiang Shi Liu Liu Huibin Lin Rujie Liu Anyan Shi 14 20 0 17 Jul 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting Marc Lelarge Léo Miolane 14 28 0 08 Jul 2019
Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning Phi Vu Tran SSL 6 16 0 25 Jun 2019
Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy Angelica I. Aviles-Rivero Nicolas Papadakis Ruoteng Li P. Sellars Samar M. Alsaleh R. Tan Carola-Bibiane Schönlieb 24 3 0 20 Jun 2019
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy Alex Lamb Vikas Verma Kenji Kawaguchi Alexander Matyasko Savya Khosla Arno Solin Yoshua Bengio AAML 30 98 0 16 Jun 2019
Selfie: Self-supervised Pretraining for Image Embedding Trieu H. Trinh Minh-Thang Luong Quoc V. Le SSL 11 111 0 07 Jun 2019
Semi-supervised semantic segmentation needs strong, varied perturbations Geoff French S. Laine Timo Aila Michal Mackiewicz G. Finlayson 26 29 0 05 Jun 2019
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training Jan Laermann Wojciech Samek Nils Strodthoff OOD 24 15 0 03 Jun 2019
Semi-Supervised Learning with Scarce Annotations Sylvestre-Alvise Rebuffi Sébastien Ehrhardt Kai Han Andrea Vedaldi Andrew Zisserman SSL 21 49 0 21 May 2019
Virtual Mixup Training for Unsupervised Domain Adaptation Xudong Mao Yun Ma Zhenguo Yang Yangbin Chen Qing Li 30 52 0 10 May 2019
S4L: Self-Supervised Semi-Supervised Learning Xiaohua Zhai Avital Oliver Alexander Kolesnikov Lucas Beyer SSL VLM 29 786 0 09 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 17 2,985 0 06 May 2019
Unsupervised Data Augmentation for Consistency Training Qizhe Xie Zihang Dai Eduard H. Hovy Minh-Thang Luong Quoc V. Le 32 2,286 0 29 Apr 2019
On Adversarial Mixup Resynthesis Christopher Beckham S. Honari Vikas Verma Alex Lamb F. Ghadiri R. Devon Hjelm Yoshua Bengio C. Pal AAML 12 12 0 07 Mar 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 199 243 0 14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 261 1,275 0 06 Mar 2017