Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Remote epitaxy is an emerging technology for producing single-crystalline, free-standing
thin films and structures. The method uses 2D van der Waals materials as semi-transparent …

Brains process information in spiking neural networks. Their intricate connections shape the
diverse functions these networks perform. Yet how network connectivity relates to function is …

The emergence of memristors with potential applications in data storage and artificial
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …

The brain is a complex system comprising a myriad of interacting neurons, posing significant
challenges in understanding its structure, function, and dynamics. Network science has …

Recent years have witnessed a surge of interest in learning representations of graph-
structured data, with applications from social networks to drug discovery. However, graph …

High‐performance organic neuromorphic devices with miniaturized device size and
computing capability are essential elements for developing brain‐inspired humanoid …

Spiking neural networks are the basis of versatile and power-efficient information processing
in the brain. Although we currently lack a detailed understanding of how these networks …

Abstract Spiking Neural Network (SNN) is considered more biologically plausible and
energy-efficient on emerging neuromorphic hardware. Recently backpropagation algorithm …

There is a growing trend to design hybrid neural networks (HNNs) by combining spiking
neural networks and artificial neural networks to leverage the strengths of both. Here, we …