New algorithm aces university math course questions
Researchers use machine learning to automatically solve, explain, and generate university-level math problems at a human level.
Researchers use machine learning to automatically solve, explain, and generate university-level math problems at a human level.
Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
Neuroscience professor and Science Hub investigator Ted Adelson explains how simulating the sense of touch with a camera can make robots smarter.
“Interpretability methods” seek to shed light on how machine-learning models make predictions, but researchers say to proceed with caution.
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.
International award supports early-career scientists and engineers as they pursue interdisciplinary works.
Professor of electrical engineering and computer science will receive additional support to advance his research and career.
Researchers have made strides toward machine-learning models that can help doctors more efficiently find information in a patient’s health record.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
Researchers created Exo for writing high-performance code on hardware accelerators.
Researchers develop a comfortable, form-fitting fabric that recognizes its wearer’s activities, like walking, running, and jumping.
Piction Health, founded by Susan Conover SM ’15, uses machine learning to help physicians identify and manage skin disease.
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
An anomaly-detection model developed by SMART utilizes machine learning to quickly detect microbial contamination.