Research
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.
Implementation of “Debiasing Item-to-Item Recommendations With Small Annotated Datasets” (RecSys ’20)
rankerEval – a Python library for evaluating rankings. A fast numpy-based implementation of ranking metrics for information retrieval and recommendation.
Archai is a platform for Neural Network Search (NAS) that allow you to generate efficient deep networks for your applications. Archai aspires to accelerate NAS research by enabling easy mix and match between different techniques…
Taoxnomic Re-annotation of NLI Examples in MultiNLI Dataset | Also on the Microsoft Download Center: https://www.microsoft.com/en-us/download/details.aspx?id=102127
InnerEye-CreateDataset contains tools to convert medical datasets in DICOM-RT format to NIFTI. Datasets converted using this tool can be consumed directly by InnerEye-DeepLearning.
CodeXGLUE is a benchmark dataset and open challenge for code intelligence. It includes a collection of code intelligence tasks and a platform for model evaluation and comparison. CodeXGLUE stands for General Language Understanding Evaluation benchmark…
MPNet: Masked and Permuted Pre-training for Language Understanding, by Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu, is a novel pre-training method for language understanding tasks. It solves the problems of MLM (masked…
At the core of our mission is the desire to create a harmonious space where conservation scientists from all over the globe can unite. Where they’re able to share, grow, use datasets and deep learning…
This project contains the training code for the Microsoft AI for Earth Species Classification API, along with the code for our API demo page (opens in new tab). This API classifies handheld photos of around 5000…