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cleanlab / cleanlab

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

data-science machine-learning data-validation exploratory-data-analysis annotations weak-supervision classification outlier-detection crowdsourcing data-cleaning active-learning data-quality image-tagging entity-recognition robust-machine-learning noisy-labels out-of-distribution-detection data-labeling label-errors data-centric-ai

Updated Mar 4, 2023
Python

weijiaheng / Advances-in-Label-Noise-Learning

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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

Updated Feb 22, 2023

Renumics / awesome-open-data-centric-ai

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Curated list of open source tooling for data-centric AI on unstructured data.

nlp computer-vision deep-learning data-visualization awesome-list outlier-detection feature-vector uncertainty-estimation active-learning data-versioning data-curation synthetic-data explainable-ai bias-detection robust-machine-learning noisy-labels data-drift data-centric-ai

Updated Mar 3, 2023

dlmacedo / entropic-out-of-distribution-detection

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A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.

machine-learning deep-learning pytorch ood osr ai-safety open-set anomaly-detection novelty-detection robust-machine-learning open-set-recognition out-of-distribution out-of-distribution-detection ood-detection trustworthy-machine-learning trustworthy-ai

Updated Sep 22, 2022
Python

tonyduan / rs4a

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Randomized Smoothing of All Shapes and Sizes (ICML 2020).

machine-learning adversarial-examples robust-machine-learning randomized-smoothing

Updated Jul 23, 2020
Jupyter Notebook

bladesteam / blades

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Blades: A simulator and benchmark for Byzantine-robust federated Learning with Attacks and Defenses Experimental Simulation

distributed-systems robust-optimization federated federated-learning robust-machine-learning byzantine-fault-tolerance federated-learning-framework fedavg federated-learning-simulator robust-federated-learning model-poisoning-attack

Updated Jan 23, 2023
Python

dlmacedo / distinction-maximization-loss

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A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.

machine-learning deep-learning pytorch classification ood osr uncertainty-estimation ai-safety open-set anomaly-detection novelty-detection robust-machine-learning open-set-recognition out-of-distribution out-of-distribution-detection ood-detection trustworthy-machine-learning trustworthy-ai

Updated Sep 22, 2022
Python

huanzhang12 / ATLA_robust_RL

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Robust Reinforcement Learning with the Alternating Training of Learned Adversaries (ATLA) framework

reinforcement-learning deep-reinforcement-learning reinforcement-learning-algorithms adversarial-examples robust-machine-learning robust-reinforcement-learning

Updated Jan 26, 2021
Python

cpwan / Attack-Adaptive-Aggregation-in-Federated-Learning

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This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.

machine-learning adversarial-attacks federated-learning robust-machine-learning

Updated Aug 21, 2021
Jupyter Notebook

suinleelab / cxr_adv

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Repository for the paper "An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs"

machine-learning radiology adversarial-machine-learning robust-machine-learning

Updated Jan 14, 2020
Python

bbenligiray / rml-cnn

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Semi-Supervised Robust Deep Neural Networks for Multi-Label Classification

semi-supervised-learning multi-label-classification loss-functions robust-machine-learning

Updated Dec 30, 2019
Python

ZFancy / SFAT

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[ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"

adversarial-learning federated-learning robust-machine-learning federated-adversarial-learning data-heterogeneity

Updated Mar 2, 2023
Python

TinfoilHat0 / Defending-Against-Backdoors-with-Robust-Learning-Rate

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The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".

machine-learning deep-learning pytorch distributed-machine-learning adversarial-attacks federated-learning robust-machine-learning backdoor-attacks

Updated Oct 3, 2022
Python

dlmacedo / robust-deep-learning

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A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.