GNN, a framework to train robust GNNs under noisy conditions. Soft-GNN mitigates label noise impact through dynamic ...

In general, gradient descent is the common algorithm used for this ... This style of neural network is also known as a cyclical graph. The backward movement opens up a variety of more ...

At ARVO 2025, in Salt Lake City, Utah, Patipol Tiyajamorn, talked about his poster on using graph neural networks to identify ...

High-entropy alloys (HEAs) offer tunable compositions and surface structures, presenting significant potential for creating ...

A review by researchers at Tongji University and the University of Technology Sydney published in Frontiers of Computer ...

WiMi's quantum algorithm provides exponential speedup in both stages, enabling neural networks to achieve convergence in significantly less time. Quantum Feedforward Propagation: Classical ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...