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.
A hybrid edge-cloud live video analytics system to empower everyone to build practical real-world video analytics applications with cutting edge machine learning algorithms.
This code is based on the paper Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model (opens in new tab). This repo is divided into two parts: PA-BELGAM: Experiments with UCI prediction alone (For…
This repository contains the source code and trained model for a large-scale pretrained dialogue response generation model. The human evaluation results (opens in new tab) indicate that the response generated from DialoGPT is comparable to human…
A High-Assurance Cryptographic Library (HACL*), a formally verified cryptographic library written in F*. This repository contains verified code for a library of modern cryptographic algorithms, including Curve25519, Ed25519, AES-GCM, Chacha20, Poly1305, SHA-2, SHA-3, HMAC, and…
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities.
GitHub Publication Publication Publication Publication Publication
The Confidential Consortium Framework (CCF) is an open-source framework for building a new category of secure, highly available, and performant applications that focus on multi-party compute and data. While not limited just to blockchain applications,…
Code to train and evaluate the GeNeVA-GAN model for the GeNeVA task proposed in our ICCV 2019 paper Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction (opens in new tab).
Petridish, is a neural architecture search (NAS) algorithm which iteratively adds shortcut connections to existing network layers. The added shortcut connections effectively perform gradient boosting on the augmented layers. The proposed algorithm is motivated by…
Sign language recognition is a challenging and often underestimated problem comprising multi-modal articulators (handshape, orientation, movement, upper body and face) that integrate asynchronously on multiple streams. Learning powerful statistical models in such a scenario requires…
