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.
This PyTorch package implements the Multi-Task Deep Neural Networks (MT-DNN) for Natural Language Understanding.
We introduce a new corpus of descriptions of Xbox avatars created by actual gamers. Each avatar is specified by 19 attributes, including clothing and body type, allowing for more than 10^20 possibilities. Using Amazon Mechanical…
Building a computer system to automatically solve math word problems written in natural language. SigmaDolphin is a project initiated in early 2013 at Microsoft Research Asia, with the primary goal of building a computer intelligent…
Microsoft TV White Spaces database enables secondary users the ability to use the TV White Spaces spectrum in order to provide for overall spectrum utilization. The design document outlines the technical implementation of the webservices…
OpenPAI is an open source platform that provides complete AI model training and resource management capabilities, it is easy to extend and supports on-premise, cloud and hybrid environments in various scale.
This code supports the paper “Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision”, presented at EMNLP 2018.
Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One example of a ubiquitous real-world application where such models are desirable is resource-scarce devices…
This download contains the processed datasets used in the AAAI’19 paper ABC: Efficient Selection of Machine Learning Configuration on Large Dataset. A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters. Given…
