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.
AIDE: Annotation Interface for Data-driven Ecology – Tools for detecting wildlife in aerial images using active learning
DiCE is a Python library that can generate counterfactual explanations for any machine learning classifier. Counterfactual explanations present “what-if” perturbations of the input such that an ML classifier outputs a different class for those perturbations…
As part of this release, Navana Tech and Microsoft Research India are open-sourcing 1648 hours of validated Odia speech dataset and a baseline model for Odia speech recognition. The speech dataset consists of recordings in…
We present a new method LiST for efficient fine-tuning of large pre-trained language models (PLMs) in few-shot learning settings. LiST significantly improves over recent methods that adopt prompt fine-tuning using two key techniques. The first…
LITMUS Predictor provides support for simulating performance in ~100 languages given training observations of the desired task-model. Each training observation specifies the finetuning-datasize + test-performance in different languages. Further, the tool provides support for constructing…
Modulo allows optimal selection of vehicles for effective drive-by sensing.
A number of PyTorch modules (neural network components) that are broadly (re)usable. The goal of this release is to provide a library to machine learning researchers to use and advance the state-of-the-art in the area.
