trustworthy-ai
There are 91 repositories under trustworthy-ai topic.
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Giskard-AI/giskard
🐢 Open-Source Evaluation & Testing for LLMs and ML models
zjunlp/EasyEdit
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
THUYimingLi/BackdoorBox
The open-sourced Python toolbox for backdoor attacks and defenses.
HowieHwong/TrustLLM
[ICML 2024] TrustLLM: Trustworthiness in Large Language Models
yunqing-me/AttackVLM
[NeurIPS-2023] Annual Conference on Neural Information Processing Systems
liuzuxin/FSRL
🚀 A fast safe reinforcement learning library in PyTorch
yunqing-me/WatermarkDM
Code of the paper: A Recipe for Watermarking Diffusion Models
verivital/nnv
Neural Network Verification Software Tool
ffhibnese/Model-Inversion-Attack-ToolBox
A comprehensive toolbox for model inversion attacks and defenses, which is easy to get started.
ml-for-high-risk-apps-book/Machine-Learning-for-High-Risk-Applications-Book
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
aiverify-foundation/aiverify
AI Verify
IBM/ai-privacy-toolkit
A toolkit for tools and techniques related to the privacy and compliance of AI models.
dlmacedo/entropic-out-of-distribution-detection
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.
qitianwu/GraphOOD-GNNSafe
The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
ai4ce/FLAT
[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory
JerryX1110/Robust-Video-Object-Segmentation
[ACM MM22] Towards Robust Video Object Segmentation with Adaptive Object Calibration, ACM Multimedia 2022
szandala/TorchPRISM
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
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.
95616ARG/SyReNN
SyReNN: Symbolic Representations for Neural Networks
AthenaCore/AwesomeResponsibleAI
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI, Trustworthy AI, and Human-Centered AI.
zhihengli-UR/StyleT2I
Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
sleeepeer/PoisonedRAG
code & data of PoisonedRAG paper
moonshot-admin/moonshot
Moonshot - A simple and modular tool to evaluate and red-team any LLM application.
zRapha/FAME
Framework for Adversarial Malware Evaluation.
sail-sg/finetune-fair-diffusion
Code of the paper: Finetuning Text-to-Image Diffusion Models for Fairness
ffhibnese/GIFD_Gradient_Inversion_Attack
[ICCV-2023] Gradient inversion attack, Federated learning, Generative adversarial network.
TMIS-Turbo/FNI-RL
[TPAMI, 2023] Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving
Crisp-Unimib/ContrXT
a tool for comparing the predictions of any text classifiers
zhihengli-UR/DebiAN
Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)
yuji-roh/fairbatch
FairBatch: Batch Selection for Model Fairness (ICLR 2021)
zhihengli-UR/discover_unknown_biases
Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
LucasFidon/trustworthy-ai-fetal-brain-segmentation
Trustworthy AI method based on Dempster-Shafer theory - application to fetal brain 3D T2w MRI segmentation
Crisp-Unimib/MERLIN
MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs.
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.
seedatnabeel/Data-IQ
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data (NeurIPS 2022)