Identifying Wrongly Predicted Samples: A Method for Active Learning

14 October 2020

Papers citing "Identifying Wrongly Predicted Samples: A Method for Active Learning"

15 / 15 papers shown

Title
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 89 36 0 17 Mar 2022
Input Similarity from the Neural Network Perspective Guillaume Charpiat N. Girard Loris Felardos Y. Tarabalka 84 73 0 10 Feb 2021
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds Jordan T. Ash Chicheng Zhang A. Krishnamurthy John Langford Alekh Agarwal BDL UQCV 85 773 0 09 Jun 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 140 3,026 0 06 May 2019
Variational Adversarial Active Learning Samarth Sinha Sayna Ebrahimi Trevor Darrell GAN DRL VLM SSL 117 579 0 31 Mar 2019
Deep Learning for Classical Japanese Literature Tarin Clanuwat Mikel Bober-Irizar A. Kitamoto Alex Lamb Kazuaki Yamamoto David R Ha 100 709 0 03 Dec 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 267 3,195 0 20 Jun 2018
Rethinking Atrous Convolution for Semantic Image Segmentation Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam SSeg 225 8,470 0 17 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 352 4,705 0 15 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 68 1,734 0 08 Mar 2017
Cost-Effective Active Learning for Deep Image Classification Keze Wang Dongyu Zhang Ya Li Ruimao Zhang Liang Lin VLM 88 678 0 13 Jan 2017
The Cityscapes Dataset for Semantic Urban Scene Understanding Marius Cordts Mohamed Omran Sebastian Ramos Timo Rehfeld Markus Enzweiler Rodrigo Benenson Uwe Franke Stefan Roth Bernt Schiele 1.1K 11,609 0 06 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 818 9,306 0 06 Jun 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,525 0 01 Sep 2014