A team of data scientists has developed a general-purpose recommendation system for insurance based on Bayesian networks and deep learning.
Researchers at UT Austin hope their computer model of COVID-19 can help other scientists in developing new drugs against the virus.
Scientists developed cryogenic memory cells that could be orders of magnitude faster than existing memories while consuming very little power.
Recent progress in density functional theory provide new insights for chemical concepts like electrophilicity, nucleophilicity, regioselectivity, stereoselectivity, and more.
Princeton scientists demonstrate that two silicon quantum bits can communicate across relatively long distances in a turning point for the technology.
Researchers design a high-performance threshold switching selector based on silver nanodots.
Resistive switching occurs when a dielectric suddenly changes its resistance in the presence of a strong electric field. This phenomenon underpins the behavior of devices such as memristors and neuromorphic memories. In Advanced Materials, Prof. Manfred Martin of...
A new study shows fundamental limitations to the computer-based simulation of chaotic systems with implications in climate change modeling, weather forecasts, and machine learning.
An updated overlook at one of the most promising building blocks for quantum technologies: fast and efficient single photon detectors.
In this WIREs Water review, the authors appraise the effectiveness with which emerging technologies and tools can (or cannot) be used to semi-automate the geomorphic analysis of rivers.