Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

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 ...