Ferroelectric hafnium and zirconium oxides have undergone rapid scientific development
over the last decade, pushing them to the forefront of ultralow-power electronic systems …

Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …

Advancements in AI led to the emergence of in-memory-computing architectures as a
promising solution for the associated computing and memory challenges. This study …

Artificial intelligence has made remarkable advancements in recent years, leading to the
development of algorithms and models capable of handling ever-increasing amounts of …

Recent advancement in emerging brain-inspired computing has pointed out a promising
path to Machine Learning (ML) algorithms with high efficiency. Particularly, research in the …

Traditional methods for identifying “hit” molecules from a large collection of potential drug-
like candidates rely on biophysical theory to compute approximations to the Gibbs free …

While Graph Neural Networks (GNNs) have demonstrated remarkable achievements in
knowledge graph reasoning, their computational efficiency on conventional computing …

In today's data-centric world, where data fuels numerous application domains, with machine
learning at the forefront, handling the enormous volume of data efficiently in terms of time …

In this paper, we present a temperature and variability-aware Verilog-A-based compact
model for simulating Ferroelectric FET. The model captures the rich physics of ferroelectric …

Machine learning and data analytics applications increasingly suffer from the high latency
and energy consumption of conventional von Neumann architectures. Recently, several in …