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 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)…
This is a deep learning toolbox to train models on medical images (or more generally, 3D images). It integrates seamlessly with cloud computing in Azure.
GitHub Video Project Project Project Project Publication Publication Publication
SMCalFlow is a large English-language dialogue dataset, featuring natural conversations about tasks involving calendars, weather, places, and people. Each turn is annotated with an executable dataflow program featuring API calls, function composition, and complex constraints…
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…
This AI for Earth project, in collaboration with the Wildlife Conservation Society Colombia (WCS Colombia) was developed to create up-to-date land cover maps of the OrinoquĂa region in Colombia. We used a land use and…
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…
This is a library for interacting with the Microsoft Embedded Social API in your Swift code.
This is a library for interacting with the Microsoft Embedded Social API in your Node.JS code.
This is a library for interacting with the Microsoft Embedded Social API in your Java code.
