Tool
Eyes First – Double Up
Use your eyes to slide all the tiles to collide like numbers to double them until you reach 2048 (or higher).
Research Tools: code, datasets, & models
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.
Tool
Eyes First – Match Two
Exercise your mind and eyes with match two! Flip cards to reveal images, and match up all the pairs to win the game.
Tool
Eyes First – Tile Slide
Practice your skills by using your eyes to slide the tiles back into order to solve the puzzles.
Dataset Source Code
Exercise Recognition from Wearable Sensors
This data set contains accelerometer and gyroscope recordings from over 200 participants performing various gym exercises. This data set is described in more detail in the associated manuscript: Morris, D., Saponas, T. S., Guillory, A.,…
Tool
Eyes First – Maze
Learn how to dwell with your eyes and navigate Lunita through each maze to help her find her way home.
Dataset Source Code
AVML (Acquire Volatile Memory for Linux)
A portable volatile memory acquisition tool for Linux. AVML is an X86_64 userland volatile memory acquisition tool written in Rust, intended to be deployed as a static binary. AVML can be used to acquire memory…
Dataset Source Code
AMDIM – Augmented Multiscale Deep InfoMax
AMDIM (Augmented Multiscale Deep InfoMax) is an approach to self-supervised representation learning based on maximizing mutual information between features extracted from multiple views of a shared context.
Dataset Source Code
MazeExplorer [1.0.0]
MazeExplorer is a customisable 3D benchmark for assessing generalisation in Reinforcement Learning. It is based on the 3D first-person game Doom and the open-source environment VizDoom. This repository contains the code for the MazeExplorer Gym…
Dataset Source Code
Dead-ends and Secure Exploration in Reinforcement Learning [1.0]
This repository hosts the code for the following ICML 2019 paper: Dead-ends and Secure Exploration in Reinforcement Learning
Dataset Source Code
Decentralized & Collaborative AI on Blockchain [1.0]
We propose a framework for participants to collaboratively build a dataset and use smart contracts to host a continuously updated model.