Recent advances at the intersection of neural networks and inverse scattering problems have transformed traditional approaches to imaging and material characterisation. Inverse scattering involves ...

(A) Left: The sharp image (ground truth) and the motion blur kernel used. Right: The noise-corrupted input images and the deblurred outputs. (B) Projection of the data onto the 2D space formed by the ...

The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables ...

Can living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir ...

It's a long time since I last worked on neural nets, and I'm working on one now for a new project.<BR><BR>I'm testing it using the good ol' XOR problem. 2 inputs, one neuron in a hidden layer, one ...

Generative artificial intelligence (AI) — such as ChatGPT and Dalle-2 — is undoubtedly one of the most groundbreaking and discussed technologies in recent history. Its applications and related issues ...

Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...

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 ...

Researchers at Tohoku University and Future University Hakodate have trained cultured rat cortical neurons to perform ...

A machine learning approach shows promise in helping astronomers infer the internal structure of stellar nurseries from ...