How symmetry can come to the aid of machine learning
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
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Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Atacama Biomaterials, co-founded by Paloma Gonzalez-Rojas SM ’15, PhD ’21, combines architecture, machine learning, and chemical engineering to create eco-friendly materials.
Although artificial intelligence in health has shown great promise, pressure is mounting for regulators around the world to act, as AI tools demonstrate potentially harmful outcomes.
MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.
A multimodal system uses models trained on language, vision, and action data to help robots develop and execute plans for household, construction, and manufacturing tasks.
MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.
This new method draws on 200-year-old geometric foundations to give artists control over the appearance of animated characters.
Justin Solomon applies modern geometric techniques to solve problems in computer vision, machine learning, statistics, and beyond.
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.