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 ...

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...

Proof of the absence of barren plateaus for a special type of quantum neural network. The work provides trainability guarantees for this architecture, meaning that one can generically train its ...

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.

“In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One ...

Mingi Kang ’26 received a Fall Research Award from Bowdoin this semester to support his project exploring how two distinct ...

Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion. They trained a convolutional neural network (CNN) with ...