Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
Multi-species Bioacoustic Classification
Multi-species bioacoustic classification using deep learning algorithms. With audio recordings collected from rainforests in Puerto Rico, we build a deep learning model that combines transfer learning and pseudo-labeling as a data augmentation technique to: 1)…
Denoised Smoothing
This repository contains the code and models necessary to replicate the results of our recent paper: Denoised Smoothing: A Provable Defense for Pretrained Classifiers Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter…
Land Cover Orinoquia
This AI for Earth project, in collaboration with the Wildlife Conservation Society Colombia (WCS Colombia (opens in new tab)) was developed to create up-to-date land cover maps of the OrinoquĂa (opens in new tab) region…
Backward Compatibility ML
The Backward Compatibility ML library is an open-source project for evaluating AI system updates in a new way for increasing system reliability and human trust in AI predictions for actions. This project’s series of loss…
Microsoft Embedded Social Swift Library for Server API
This is a library for interacting with the Microsoft Embedded Social API in your Swift code.
Microsoft Embedded Social Node.JS Library for Server API
This is a library for interacting with the Microsoft Embedded Social API in your Node.JS code.