By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Yann LeCun is a leading AI voice whose pathbreaking work in neural networks became the foundation for modern computers and deep learning.| India News ...

Home > Pressemitteilung: Machine Learning Helps Solve Central ...

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in real scenarios.

My tryst with AI began during my Master’s (1988–90) and subsequent PhD at IIT Delhi (1991–95). Under the mentorship of stalwarts like Prof. Madan Gopal and Prof. Santanu Chaudhury, I dove into the ...

Now, what makes it complicated is that the wealth may be created in some countries (but) jobs lost in another country. A global redistribution (plan) is right now out of sight, he told Moneycontrol in ...

Companies are hatching the problems one after the other. They don't really have an answer to the question, ‘Is this going to be safe?’ They don't know,” he told Moneycontrol in an interview.

Your brain calculates complex physics every day and you don't even notice. This neuromorphic chip taps into the same idea.

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving neutron diffusion equations, yet their accuracy and stability are often hindered by limited spatial ...