FR-Train: A Mutual Information-Based Approach to Fair and Robust Training (ICML 2020)
-
Updated
Jun 3, 2021 - Jupyter Notebook
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training (ICML 2020)
Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
Reliable and Trustworthy Intelligence AI notebooks from ETH Zurich course taught by Prof. Dr. Martin Vechev
Notes, references, and materials about Differential Privacy that I found useful for my research. Recommendations are welcome.
Sample Selection for Fair and Robust Training (NeurIPS 2021)
Rule Extraction from Bayesian Networks
Codes and Datasets for our WSDM 2022 Paper: "MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs"
[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory
a tool for comparing the predictions of any text classifiers
Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
Paper Summary for Relations between Trustworthy AI Concepts
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.
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.
Paper list and relevant material for Privacy-Preserving Computation.
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.
Code from PLDI '21 paper "Provable Repair of Deep Neural Networks."
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
Stash of some of the most potent research papers, blogs and videos on AI which I liked.
Add a description, image, and links to the trustworthy-ai topic page so that developers can more easily learn about it.
To associate your repository with the trustworthy-ai topic, visit your repo's landing page and select "manage topics."