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.
Source code for our CRISPR off-target prediction model, Elevation
Visual Studio Tools for AI is a free Visual Studio extension to build, test, and deploy deep learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not…
Python module applying deep learning to improve clustering and other analysis of single-cell genomic data (gene expression and copy number variation).
This is DLT, a dual learning toolkit developed by Microsoft Research. Dual learning leverages the structure duality among AI tasks (e.g., English-to-French translation vs. French-to-English translation, speech recognition vs. text to speech, and image classification…
Use consumer video equipment to trace animal movement. Source code of the project that has been released in precompiled binary form in 2014 https://www.microsoft.com/en-us/download/details.aspx?id=52266
Detours is a software package for monitoring and instrumenting API calls on Windows. Detours has been used by many ISVs and is also used by product teams at Microsoft. Detours is now available under a…
MASS is a novel pre-training method for sequence to sequence based language generation tasks. It randomly masks a sentence fragment in the encoder, and then predicts it in the decoder.
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal to…
