We propose a new machine-learning-based approach for forecasting Value-at-Risk (VaR) named CoFiE-NN where a neural network (NN) is combined with Cornish-Fisher expansions (CoFiE). CoFiE-NN can capture ...

For decades, schizophrenia and bipolar disorder have been diagnosed from the outside in, through behavior, mood, and memory ...

A new study shows that the physics principle of 'nucleation' can perform complex calculations that rival a simple neural network. The work may suggest avenues for new ways to think about computation ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

As digital banking becomes increasingly at the heart of contemporary financial systems, the imperative to address accelerating cybersecurity threats and regulatory complexity has only grown more ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.