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Some thing interesting about trustworthy-ai
Some thing interesting about trustworthy-ai
trustworthy-ai,Code from PLDI '23 paper "Architecture-Preserving Provable Repair of Deep Neural Networks."
Organization: 95616arg
trustworthy-ai,Code from PLDI '21 paper "Provable Repair of Deep Neural Networks."
Organization: 95616arg
trustworthy-ai,SyReNN: Symbolic Representations for Neural Networks
Organization: 95616arg
trustworthy-ai,[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory
Organization: ai4ce
Home Page: https://ai4ce.github.io/FLAT/
trustworthy-ai,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 and Human-Centered AI.
Organization: athenacore
trustworthy-ai,a tool for comparing the predictions of any text classifiers
User: crisp-unimib
trustworthy-ai,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.
User: crisp-unimib
Home Page: https://crispresearch.it/
trustworthy-ai,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.
User: dlmacedo
trustworthy-ai,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.
User: dlmacedo
trustworthy-ai,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.
User: dlmacedo
trustworthy-ai,Package to accelerate research on generalized out-of-distribution (OOD) detection.
User: edadaltocg
Home Page: http://detectors.readthedocs.io/
trustworthy-ai,[ICCV-2023] Gradient inversion attack, Federated learning, Generative adversarial network.
User: ffhibnese
trustworthy-ai,A comprehensive toolbox for model inversion attacks and defenses, which is easy to get started.
User: ffhibnese
trustworthy-ai,🐢 Open-Source Evaluation & Testing framework for LLMs and ML models
Organization: giskard-ai
Home Page: https://docs.giskard.ai
trustworthy-ai,Rule Extraction from Bayesian Networks
User: hayesall
Home Page: https://hayesall.com/blog/bayes-net-rule-extraction/
trustworthy-ai,(ICML 2024) TrustLLM: Trustworthiness in Large Language Models
User: howiehwong
Home Page: https://trustllmbenchmark.github.io/TrustLLM-Website/
trustworthy-ai,A toolkit for tools and techniques related to the privacy and compliance of AI models.
Organization: ibm
Home Page: https://aip360.res.ibm.com
trustworthy-ai,AutoML system for building trustworthy peptide bioactivity predictors
Organization: ibm
Home Page: https://ibm.github.io/AutoPeptideML/
trustworthy-ai,AI Verify
Organization: imda-btg
Home Page: https://imda-btg.github.io/aiverify/
trustworthy-ai,
Organization: imda-btg
Home Page: https://imda-btg.github.io/aiverify-developer-tools/
trustworthy-ai,[ACM MM22] Towards Robust Video Object Segmentation with Adaptive Object Calibration, ACM Multimedia 2022
User: jerryx1110
trustworthy-ai,[ICCV 2023] Partition-and-Debias: Agnostic Biases Mitigation via a Mixture of Biases-Specific Experts
User: jiaxuan-li
trustworthy-ai,Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts (Official Pytorch Implementation)
User: joycenerd
Home Page: https://joycenerd.github.io/prompting4debugging/
trustworthy-ai,🚀 A fast safe reinforcement learning library in PyTorch
User: liuzuxin
Home Page: https://fsrl.readthedocs.io
trustworthy-ai,Trustworthy AI method based on Dempster-Shafer theory - application to fetal brain 3D T2w MRI segmentation
User: lucasfidon
trustworthy-ai,Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
Organization: ml-for-high-risk-apps-book
trustworthy-ai,Moonshot - A simple and modular tool to evaluate and red-team any LLM application.
User: moonshot-admin
trustworthy-ai,Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization
Organization: nlp2ct
Home Page: https://arxiv.org/abs/2305.01951
trustworthy-ai,Paper list and relevant material for Privacy-Preserving Computation.
User: pengyuan-zhou
trustworthy-ai,The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
User: qitianwu
trustworthy-ai,An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.
User: riccardospolaor
trustworthy-ai,Code of the paper: Finetuning Text-to-Image Diffusion Models for Fairness
Organization: sail-sg
Home Page: https://sail-sg.github.io/finetune-fair-diffusion/
trustworthy-ai,Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data (NeurIPS 2022)
User: seedatnabeel
trustworthy-ai,TRIAGE: Characterizing and auditing training data for improved regression (NeurIPS 2023)
User: seedatnabeel
trustworthy-ai,code & data of PoisonedRAG paper
User: sleeepeer
Home Page: https://arxiv.org/abs/2402.07867
trustworthy-ai,Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
User: szandala
Home Page: https://pypi.org/project/torchprism
trustworthy-ai,The open-sourced Python toolbox for backdoor attacks and defenses.
User: thuyimingli
trustworthy-ai,[TPAMI, 2023] Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving
User: tmis-turbo
trustworthy-ai,Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Organization: trusted-ai
Home Page: https://adversarial-robustness-toolbox.readthedocs.io/en/latest/
trustworthy-ai,Neural Network Verification Software Tool
Organization: verivital
Home Page: http://www.verivital.com
trustworthy-ai,Sample Selection for Fair and Robust Training (NeurIPS 2021)
User: yuji-roh
trustworthy-ai,FairBatch: Batch Selection for Model Fairness (ICLR 2021)
User: yuji-roh
trustworthy-ai,FR-Train: A Mutual Information-Based Approach to Fair and Robust Training (ICML 2020)
User: yuji-roh
trustworthy-ai,[NeurIPS-2023] Annual Conference on Neural Information Processing Systems
User: yunqing-me
Home Page: https://arxiv.org/pdf/2305.16934.pdf
trustworthy-ai,Code of the paper: A Recipe for Watermarking Diffusion Models
User: yunqing-me
Home Page: https://yunqing-me.github.io/WatermarkDM/
trustworthy-ai,Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)
User: zhihengli-ur
trustworthy-ai,Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
User: zhihengli-ur
trustworthy-ai,Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
User: zhihengli-ur
trustworthy-ai,An Easy-to-use Knowledge Editing Framework for LLMs.
Organization: zjunlp
Home Page: https://zjunlp.github.io/project/KnowEdit
trustworthy-ai,Framework for Adversarial Malware Evaluation.
User: zrapha
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