[AAAI 2023] An official PyTorch implementation of paper 'READ: Aggregating Reconstruction Error into Out-of-distribution Detection'
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Updated
May 30, 2023 - Python
[AAAI 2023] An official PyTorch implementation of paper 'READ: Aggregating Reconstruction Error into Out-of-distribution Detection'
Paper Summary for Relations between Trustworthy AI Concepts
Unofficial implementation of paper "Flexibly Fair Representation Learning by Disentanglement"
Python package to accelerate research on generalized out-of-distribution (OOD) detection.
This repo contains the codes, figures and datasets for the paper - U-Trustworthy Models. Reliability, Competence, and Confidence in Decision-Making.
Neural Additive Models - Visualization Tool in PyTorch/Plotly-Dash
Machine Learning Security Library
[AAAI'23 Paper] A machine learning defense for auditors of black box automated decision-making systems.
An open source web platform for assessing Responsible and Trustworthy AI maturity level
ObscurePrompt: Jailbreaking Large Language Models via Obscure Input
Optimization-based deep learning models can give explainability with output guarantees and certificates of trustworthiness.
Stash of some of the most potent research papers, blogs and videos on AI which I liked.
Scripts to process the reference framework into an object
DSPLab@UMich-Dearborn Website
Official implementation of NeurIPS 2023 paper "Trade-off Between Efficiency and Consistency for Removal-based Explanations" (https://arxiv.org/abs/2210.17426)
Code from PLDI '23 paper "Architecture-Preserving Provable Repair of Deep Neural Networks."
FairPy: A Python Library for Machine Learning Fairness
We make Generative AI accessible to Federal agencies and businesses. Easy-to-use ezGPT™ platform eliminates the need for in-house expertise and delivers pre-built solutions for rapid innovation. With security and privacy at its core, we unlock the potential of AI. Our innovative chatbot guides users, ensuring a smooth and successful experience.
Code for paper "FreezeAsGuard: Mitigating Illegal Adaptation of Diffusion Models via Selective Tensor Freezing"
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