A curated list of resources for Learning with Noisy Labels
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May 3, 2024
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robust-learning
Here are 22 public repositories matching this topic...
A curated (most recent) list of resources for Learning with Noisy Labels
deep-neural-networks deep-learning conference paper weakly-supervised-learning robustness international-conference noisy-data label-noise robust-machine-learning noisy-labels noisy-label-learning learning-with-noisy-labels unreliable-labels robust-learning learning-with-label-noise
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Oct 18, 2024
Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels
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May 22, 2023 - Python
[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark
nlp machine-learning deep-learning weak-supervision dataset benchmark-framework sequence-labeling weakly-supervised-learning data-programming robust-learning data-centric-ai
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Feb 13, 2024 - Python
A curated list of resources for model inversion attack (MIA).
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Dec 24, 2024
[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
deep-neural-networks deep-learning pytorch icml noisy-data label-noise noisy-labels unreliable-labels robust-learning icml-2020
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Jul 5, 2024 - Python
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
deep-learning graph-convolutional-networks adversarial-attacks graph-neural-networks robust-learning
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Jul 6, 2023 - Python
Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (ICML 2020)
machine-learning black-box-optimization social-good robust-learning icml-2020 limited-transfer-learning medical-imaging-classification
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Nov 14, 2020 - Python
AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
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Jun 9, 2021 - Python
A curated list of Robust Machine Learning papers/articles and recent advancements.
machine-learning deep-learning healthcare awesome-list ood fairness covariate-shift federated-learning machine-learning-bias fairness-testing bias-detection robust-machine-learning fairness-ai concept-shift fairness-ml robust-learning label-shift data-shift distribution-shift healthcare-federated-learning
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Oct 13, 2022
AAAI 2021: Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
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Jun 9, 2021 - Python
Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
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Mar 24, 2023 - Python
awesome awesome-list awesome-lists backdoor-attacks robust-learning data-poisoning data-poisoning-attacks
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Sep 21, 2022
Source code for Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022.
deep-learning pytorch recommender-system implicit-feedback denoising graph-neural-networks robust-learning sigir2022
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Jul 10, 2022 - Python
[Re] Can gradient clipping mitigate label noise? (ML Reproducibility Challenge 2020)
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Sep 3, 2024 - Python
"RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning" by Yue Duan (ECCV 2022)
machine-learning deep-learning pytorch semi-supervised-learning robust-machine-learning entropy-regularizer robust-learning semi-supervised-classification distribution-shift eccv2022
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Nov 30, 2024 - Python
Code for "Adversarial Robustness via Runtime Masking and Cleansing" (ICML 2020)
security neural-network convolutional-neural-networks adversarial-learning adversarial-attacks tensorflow2 adversarial-defense robust-learning icml-2020
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Mar 25, 2023 - Jupyter Notebook
Adversarial Attacks and Defenses via Image perturbations
convolutional-neural-networks defense adversarial-examples data-corruption adversarial-perturbations adversarial-training adversarial-attack diffusion-models robust-learning vision-transformer vision-language-model
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Nov 4, 2024
Corruption Robust Image Classification with a new Activation Function. Our proposed Activation Function is inspired by the Human Visual System and a classic signal processing fix for data corruption.
cnn classification data-augmentation relu-layer activation-functions robust-learning distorted-images image-corruption
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Jun 23, 2021 - MATLAB
Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS
clustering statistical-learning prediction artificial-intelligence statistical-inference neural-networks skew-t unsupervised-learning em-algorithm non-linear-regression t-distribution mixture-of-experts skewed-data robust-learning skew-normal
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Feb 13, 2020 - R
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