Memristive devices, which combine a resistor with memory functions such that voltage
pulses can change their resistance (and hence their memory state) in a nonvolatile manner …

Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Many in-memory computing frameworks demand electronic devices with specific switching
characteristics to achieve the desired level of computational complexity. Existing memristive …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Continually learning new classes from fresh data without forgetting previous knowledge of
old classes is a very challenging research problem. Moreover, it is imperative that such …

This two-part comprehensive survey is devoted to a computing framework most commonly
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …

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

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 …

Machine learning, particularly in the form of deep learning (DL), has driven most of the
recent fundamental developments in artificial intelligence (AI). DL is based on computational …

Neither deep neural networks nor symbolic artificial intelligence (AI) alone has approached
the kind of intelligence expressed in humans. This is mainly because neural networks are …