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 repository houses the supporting code for the paper Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent. The Dense Gradient Tree (DGT) technique supports learning decision trees of a given height for…
This project contains example notebooks exhibiting confidence sequences that are robust, i.e., converge for observations with infinite variance. Robust Mean Demo: The basic technique for covering the running conditional mean in a nonstationary environment. Includes…
Large-scale pretrained models for goal-directed dialog. This repository showcases building goal-directed dialog using GODEL, and contains the dataset, source code and pre-trained model for the following paper: GODEL: Large-Scale Pre-Training for Goal-Directed Dialog
This repo contains the code for the video analysis pipeline for the paper Towards Automating Retinoscopy for Refractive Error Diagnosis accepted at the IMWUT 2022. The input to the system is a retinoscopic video, with the patient wearing…
BioGPT is a pre-trained language model for text mining and generation for biomedical domain research.
Motivated by our recent work (opens in new tab), we are releasing a repository for training transformer models with differential privacy. Our repository is based on integrating the Opacus library (opens in new tab) to the Hugging Face (opens…
This toolbox aims at providing low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It helps to simplify and streamline work on deep learning models for healthcare and life sciences, by…
Source code of BindVAE paper on Variational Auto Encoders for learning binding signatures of transcription factors. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02723-w
