Older models struggled with depth issues in 2D images, but the novel neural network handles these problems with ease.

If AI systems can do their own AI research, they can come up with superior AI architectures and methods. Via a simple ...

Accurately modeling particle movement through fluids is crucial in fields ranging from chemical engineering to aerospace. The ...

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now ...

A deep neural network was trained using quantum tunneling to mimic the human ability to view optical illusions.

Dynamical models, mathematical or computational approaches ... nonlinear dynamical modeling framework based on recurrent ...

Relief-type cultural heritage objects are commonly found in many historical sites worldwide, but often suffer from varying levels of damage and deterioration. Traditional methods for image ...

Professor Yong-Hoon Kim's team from the School of Electrical Engineering succeeded for the first time in accelerating quantum ...

By constructing and training neural network models, predictive models for three clinical outcomes were developed, and the researchers successfully predicted the objective response rate (ORR ...

Haiper 2.0, the new model that the company debuted today, is based on a so-called DiT architecture. This is an approach to ...