For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

In principle it's possible to create a neural network classifier for MNIST data using just a single linear layer that accepts 784 input values and emits 10 logits or pseudo-probabilities. But this ...

The great breakthrough about this model is that it makes no assumption about input data type, while, for instance, existing convolutional neural networks work for images only. Source: Perceiver ...

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

The neural network shown in Figure 2 is most often called a two-layer network (rather than a three-layer network, as you might have guessed) because the input layer doesn't really do any processing. I ...

This may also explain why adding more layers to the light-based neural network had a very modest impact on accuracy. Overall, it's extremely impressive that this works at all.

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.

Comparison with ground truth: Neural network-produced CT ventilation images (a–c) and Galligas PET ventilation images (d–f) for a high-correlation case. (Courtesy: CC BY 4.0/Med. Phys.