On the road to cleaner, greener, and faster driving
Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.
Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.
Researchers devise an efficient protocol to keep a user’s private information secure when algorithms use it to recommend products, songs, or shows.
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
Researchers create a mathematical framework to evaluate explanations of machine-learning models and quantify how well people understand them.
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
A new neural network approach captures the characteristics of a physical system’s dynamic motion from video, regardless of rendering configuration or image differences.
Their model’s predictions should help researchers improve ocean climate simulations and hone the design of offshore structures.
Workshop hosted by MIT’s Climate and Sustainability Consortium, MIT-IBM Watson AI Lab, and the MIT Schwarzman College of Computing highlights how new approaches to computing can save energy and help the planet.
Competitive seed grants launch yearlong investigations of novel hypotheses about potential causes, biomarkers, treatments of Alzheimer’s and ALS.
Linking techniques from machine learning with advanced numerical simulations, MIT researchers take an important step in state-of-the-art predictions for fusion plasmas.
A new artificial intelligence technique only proposes candidate molecules that can actually be produced in a lab.
MIT researchers can now estimate how much information data are likely to contain, in a more accurate and scalable way than previous methods.
Researchers have developed a technique that enables a robot to learn a new pick-and-place task with only a handful of human demonstrations.
MIT CSAIL scientists created an algorithm to solve one of the hardest tasks in computer vision: assigning a label to every pixel in the world, without human supervision.
A new machine-learning system may someday help driverless cars predict the next moves of nearby drivers, cyclists, and pedestrians in real-time.