Using machine learning to identify promising polymer membranes

Polymer membranes are commonly used in industry for the separation of gases like CO2 from flue gas and methane from natural gas. Over several decades, researchers have been studying various polymers to improve their permeability ...

Deep learning applied to drug discovery and repurposing

In a recently accepted manuscript titled "Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data", scientists from Insilico Medicine, Inc located at the ...

Enhanced video quality despite poor network conditions

Professor Jinwoo Shin and Professor Dongsu Han from the School of Electrical Engineering developed neural adaptive content-aware internet video delivery. This technology is a novel method that combines adaptive streaming ...

Neural networks predict planet mass

To find out how planets form, astrophysicists run complicated and time-consuming computer calculations. Members of the NCCR PlanetS at the University of Bern have now developed a totally novel approach to speed up this process ...

Where deep learning meets metamaterials

Breakthroughs in the field of nanophotonics—how light behaves on the nanometer scale—have paved the way for the invention of "metamaterials," man-made materials that have enormous applications, from remote nanoscale sensing ...

A high-throughput AI method for leaf counting

In cereal crops, the number of new leaves each plant produces is used to study the periodic events that constitute the biological life cycle of the crop. The conventional method of determining leaf numbers involves manual ...

Deep neural network to find hidden turbulent motion on the sun

Scientists developed a neural network deep learning technique to extract hidden turbulent motion information from observations of the sun. Tests on three different sets of simulation data showed that it is possible to infer ...

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