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Projects in Awesome Lists tagged with trustworthy-machine-learning
A curated list of projects in awesome lists tagged with trustworthy-machine-learning .
https://github.com/THUYimingLi/BackdoorBox
The open-sourced Python toolbox for backdoor attacks and defenses.
backdoor-attacks backdoor-defenses backdoor-learning trustworthy-ai trustworthy-machine-learning
Last synced: 31 Jul 2024
https://github.com/HowieHwong/TrustLLM
[ICML 2024] TrustLLM: Trustworthiness in Large Language Models
ai benchmark dataset evaluation large-language-models llm natural-language-processing nlp pypi-package toolkit trustworthy-ai trustworthy-machine-learning
Last synced: 03 Aug 2024
https://github.com/ENSTA-U2IS-AI/torch-uncertainty
Open-source framework for uncertainty and deep learning models in PyTorch :seedling:
bayesian-network computer-vision ensembles mixup neural-networks predictive-uncertainty pytorch reliable-ai trustworthy-machine-learning uncertainty uncertainty-quantification
Last synced: 01 Aug 2024
https://github.com/dlmacedo/distinction-maximization-loss
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.
ai-safety anomaly-detection classification deep-learning machine-learning novelty-detection ood ood-detection open-set open-set-recognition osr out-of-distribution out-of-distribution-detection pytorch robust-machine-learning trustworthy-ai trustworthy-machine-learning uncertainty-estimation
Last synced: 01 Aug 2024
https://github.com/LucasFidon/trustworthy-ai-fetal-brain-segmentation
Trustworthy AI method based on Dempster-Shafer theory - application to fetal brain 3D T2w MRI segmentation
deep-learning fetal-mri segmentation trustworthy-ai trustworthy-machine-learning
Last synced: 02 Aug 2024
https://github.com/dlmacedo/robust-deep-learning
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.
anomaly-detection classification deep-learning deep-neural-networks machine-learning novelty-detection ood-detection open-set open-set-recognition out-of-distribution out-of-distribution-detection pytorch robust-deep-learning robust-machine-learning trustworthy-ai trustworthy-machine-learning uncertainty-calibration uncertainty-estimation uncertainty-neural-networks
Last synced: 01 Aug 2024