Abstract Generative Artificial Intelligence (GAI) is attracting the increasing attention of
materials community for its excellent capability of generating required contents. With the …

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development
and risk assessment of environmental chemicals. PBPK model development requires the …

Nonlinear phenomena in physical systems can be used for brain-inspired computing with
low energy consumption. Response from the dynamics of a topological spin structure called …

Beyond-CMOS computational paradigms are necessary to solving the problems that we face
with modern computers in achieving scalability, low energy consumption, reduced latency …

Neural networks have revolutionized the area of artificial intelligence and introduced
transformative applications to almost every scientific field and industry. However, this …

The rapid development in the field of artificial intelligence has increased the demand for
neuromorphic computing hardware and its information‐processing capability. A spintronics …

Physical reservoir computing is a framework that enables energy‐efficient information
processing by using physical systems. Nonlinear dynamics in physical systems provide a …

Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects
have attracted considerable interest regarding solving complex tasks efficiently. Particularly …

Quantum reservoir computing is a promising approach for quantum neural networks,
capable of solving hard learning tasks on both classical and quantum input data. However …

Abstract Physical Reservoir Computing (PRC) is an unconventional computing paradigm
that exploits the nonlinear dynamics of reservoir blocks to perform temporal data …