This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be replaced with ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

Western researchers have developed a novel technique using math to understand exactly how neural networks make decisions—a ...

This important work substantially advances our understanding of episodic memory by proposing a biologically plausible mechanism through which hippocampal barcode activity enables efficient memory ...

Two new neural network designs promise to make AI models more adaptable and efficient, potentially changing how artificial ...

Artificial intelligence is everywhere, from the personal assistant in your pocket to self-driving cars navigating busy ...

The Chinese Canadian artist is presenting a new kinetic work as part of the arts and culture programme at the 2025 World ...

FDA published a draft guidance titled “Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management ...

To address the above problems, this article proposes a recurrent self-coding neural network (RSCN) for one-stop noise cancellation of the whole measurement line signal. The method adopts the gated ...