Chemical engineers have developed a machine-learning model that can accurately predict the heat capacity of the versatile metal-organic framework materials.
A discussion of the significant legal scrutiny and numerous safeguards most workers’ data collection and processing activities would need to meet, as falling within the scope of high-risk AI systems.
Using satellite images from before a storm and real-time images, together with machine learning, to create a disaster monitoring system that can map damage.
Ana Lucic has developed a framework for explaining predictions of machine learning models that could improve heart examinations for underserved communities.
Engineers from the University of Cambridge have developed a machine learning algorithm that can detect and correct a wide variety of different errors in real time.
Using Graph Neural Networks, we trained Generative Adversarial Networks to correctly predict the coherent orientations of galaxies in a state-of-the-art cosmological simulation.
We present auton-survival – a comprehensive Python code repository of user-friendly, machine learning tools for working with censored time-to-event data.