Our resident data scientist explains how to train neural networks with two popular variations of the back-propagation technique: batch and online. Training a neural network is the process of ...

With the help of Python and the NumPy add-on package, I'll explain how to implement back-propagation training using momentum. Neural network momentum is a simple technique that often improves both ...

If today's college students could find a way to get their hands on a copy of Facebook's latest neural network, they could cheat all the way through Calc 3. They could even solve the differential ...

Here’s a challenge for the mathematically inclined among you. Solve the following differential equation for y: You have 30 seconds. Quick! No dallying. The answer, of course, is: If you were unable to ...

More than 70 years ago, researchers at the forefront of artificial intelligence research introduced neural networks as a revolutionary way to think about how the brain works. In the human brain, ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster. In high ...

Partial differential equations can describe everything from planetary motion to plate tectonics, but they’re notoriously hard to solve. Unless you’re a physicist or an engineer, there really isn’t ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...