MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced that they have developed a set of quantum algorithms for feedforward neural networks, breaking through the performance ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

The two-chip system includes a 16-channel photonic neuromorphic chip with 272 trainable parameters, giving it the ability to process multiple streams of optical signals at once and adjust many ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

John J. Hopfield and Geoffrey E. Hinton received the Nobel Prize in physics on Oct. 8, 2024, for their research on machine learning algorithms and neural networks that help computers learn. Their work ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

Researchers from KAIST and UC Berkeley have developed a neural network-based method to correct optical distortions in deep tissue microscopy without additional hardware. The system uses Neural Fields ...

Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

Researchers from Skoltech and the Shanghai Institute of Optics and Fine Mechanics have developed an approach that helps ...

The future of conflict prediction relies on combining technical ability, institutional governance and ethical responsibility.