Strengthening electron-triggered light emission
A new method can produce a hundredfold increase in light emissions from a type of electron-photon coupling, which is key to electron microscopes and other technologies.
A new method can produce a hundredfold increase in light emissions from a type of electron-photon coupling, which is key to electron microscopes and other technologies.
Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.
MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
CAST Visiting Artist Andreas Refsgaard engages the MIT community in the ethics and play of creative coding.
This year's fellows will work across research areas including telemonitoring, human-computer interactions, operations research, AI-mediated socialization, and chemical transformations.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
Researchers at the Center for Theoretical Physics lead work on testing quantum gravity on a quantum processor.
Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.
New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
New technique could diminish errors that hamper the performance of super-fast analog optical neural networks.
MIT undergraduate researchers Helena Merker, Harry Heiberger, and Linh Nguyen, and PhD student Tongtong Liu, exploit machine-learning techniques to determine the magnetic structure of materials.
The MIT senior will pursue postgraduate studies in computer science in Ireland.
New research reveals a scalable technique that uses synthetic data to improve the accuracy of AI models that recognize images.
New system can teach a group of cooperative or competitive AI agents to find an optimal long-term solution.