deep_learning_with_noisy_labels_literature
Deep Learning Study
A collection of papers and repos on deep learning with noisy labels.
This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.
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last commit: over 3 years ago
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subeeshvasu/awesome-learning-with-label-noiseRelated projects:
| Repository | Description | Stars |
|---|---|---|
 chenpf1025/noisy_label_understanding_utilizing | An investigation into deep learning models trained with noisy labels and methods to improve their accuracy. | 90 |
 weijiaheng/advances-in-label-noise-learning | A curated collection of papers and resources on learning with noisy labels in machine learning | 696 |
 dr-darryl-wright/noisy-labels-with-bootstrapping | An implementation of training deep neural networks on noisy labels with bootstrapping using Keras | 22 |
| chenpf1025/idn | Provides tools and data for studying instance-dependent label noise in deep neural networks, with a focus on combating noisy labels | 35 |
 pimentel/deep_learning_papers | A collection of papers on deep learning applications in computational biology | 185 |
 uds-lsv/multi-tasking_learning_with_unreliable_labels | An open source software project that extends an existing algorithm to handle noisy labels in machine learning for low-resource data generation. | 8 |
 udibr/noisy_labels | This project explores how to adapt neural networks to noisy labels by introducing a mechanism that can learn to correct the errors. | 118 |
 kthyeon/fine_official | Implementation of a method to improve machine learning models trained with noisy labels by selecting and collaborating with high-quality samples | 39 |
 dathoangnd/gonet | A Go module implementing a multi-layer Neural Network for machine learning tasks | 82 |
 delchiaro/training-cnn-noisy-labels-keras | An implementation of a deep learning training method for handling noisy labels in convolutional neural networks using the VGG-16 network architecture. | 6 |
 hjimce/o2u-net | An approach to detect noise in labels used with deep neural networks during training | 77 |
 google-deepmind/jraph | A lightweight library for working with graph neural networks in jax. | 1,380 |
 nust-machine-intelligence-laboratory/jo-src | An implementation of a contrastive learning approach to address noisy labels in machine learning models | 5 |
 vdenberg/noisy-label-neural-network | An implementation of a neural network algorithm designed to improve performance on noisy labeled data | 3 |
 mzaradzki/neuralnets | An experiment with various deep learning libraries and frameworks on images and time series data | 162 |