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Ranking-based-Instance-Selection
Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21
Github repo for webly labeled learning of sound events
A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018
This repository contains the pytroch code to reproduce the results the paper "Wasserstein Adversarial Regularization for Learning with Label Noise"
The main features of bbdamodaran/war are: Robust Learning Frameworks.
Open-source alternatives to bbdamodaran/war include: alibaba-edu/ranking-based-instance-selection — Ranking-based-Instance-Selection. antoninbrthn/csidn — Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21. anuragkr90/webly-labeled-sounds — Github repo for webly labeled learning of sound events. arghosh/robustmw-net — WACV'21: Do We Really Need Gold Samples for Sample Weighting Under Label Noise? automl-4paradigm/s2e — Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML… alfredxiangwu/lightcnn — A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018.