trustworthy-ai
Here are 91 public repositories matching this topic...
This repo contains the codes, figures and datasets for the paper - U-Trustworthy Models. Reliability, Competence, and Confidence in Decision-Making.
-
Updated
Dec 15, 2023 - Jupyter Notebook
Paper Summary for Relations between Trustworthy AI Concepts
-
Updated
Sep 2, 2022
DSPLab@UMich-Dearborn Website
-
Updated
Dec 27, 2023 - HTML
FairPy: A Python Library for Machine Learning Fairness
-
Updated
Mar 1, 2023
Human vs AI: Frontend📱
-
Updated
May 17, 2023 - TypeScript
Trustworthy AI/ML course by Professor Birhanu Eshete, University of Michigan, Dearborn.
-
Updated
May 10, 2024 - HTML
A robustness study of selected SDG classifiers
-
Updated
Apr 4, 2023
Code for the Paper "A Functional Data Perspective and Baseline on Multi-Layer Out-of-Distribution Detection"
-
Updated
Aug 2, 2023 - Python
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.
-
Updated
Feb 8, 2024 - HTML
Birhanu Eshete is an Associate Professor of Computer Science at the University of Michigan, Dearborn. His main research focus is in trustworthy machine learning with emphasis on security, safety, privacy, interpretability, fairness, and the dynamics thereof. He also studies online cybercrime and advanced and persistent threats (APTs).
-
Updated
May 23, 2024 - HTML
Neural Additive Models - Visualization Tool in PyTorch/Plotly-Dash
-
Updated
Mar 3, 2023 - Python
Unofficial implementation of paper "Flexibly Fair Representation Learning by Disentanglement"
-
Updated
Sep 16, 2023 - Python
Scripts to process the reference framework into an object
-
Updated
Oct 3, 2023 - Python
subMFL: Compatible subModel Generation for Federated Learning in Device Heterogeneous Environment
-
Updated
Apr 29, 2024 - Jupyter Notebook
Runtime data integration system that empowers any data processing system to capture and query workflow provenance using data observability.
-
Updated
May 15, 2024 - Python
Reliable and Trustworthy Intelligence AI notebooks from ETH Zurich course taught by Prof. Dr. Martin Vechev
-
Updated
Nov 7, 2021 - Jupyter Notebook
EditBias: Debiasing Stereotyped Language Models via Model Editing
-
Updated
Mar 19, 2024 - Python
This repo contains the code for "Houston we have a Divergence: A Subgroup Performance Analysis of ASR Models"
-
Updated
Apr 6, 2024 - Jupyter Notebook
Improve this page
Add a description, image, and links to the trustworthy-ai topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the trustworthy-ai topic, visit your repo's landing page and select "manage topics."