Nature

Neural Networks and Inverse Scattering Problems

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

DNA-based neural network learns from examples to solve problems

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...
Psychology Today

Why the New Artificial Intelligence Is So Powerful

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...
EurekAlert!

KAIST proposes a new way to circumvent a long-time frustration in neural computing

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 ...
The Scientist

Artificial Neural Networks: Learning by Doing

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
SDxCentral

AI has a long-term memory problem (how to make neural networks less forgetful)

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 ...
Visual Studio Magazine

Create a Working Neural Network Prediction System with C#

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 ...
Ars Technica

Neural networks: How difficult is the XOR problem?

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 ...
Visual Studio Magazine

Neural Network Regression from Scratch Using C#

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 ...