Attention has arguably become one of the most important concepts in the deep learning
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …

Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …

Deep neural networks (DNNs) are an indispensable machine learning tool despite the
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …

Artificial intelligence (AI) has significantly impacted various fields. Large language models
(LLMs) like GPT-4, BARD, PaLM, Megatron-Turing NLG, Jurassic-1 Jumbo etc., have …

Black hat hackers use malicious exploits to circumvent security controls and take advantage
of system vulnerabilities worldwide, costing the global economy over $450 billion annually …

Despite some successful applications of goal-driven navigation, existing deep reinforcement
learning (DRL)-based approaches notoriously suffers from poor data efficiency issue. One of …

Advances in applied machine learning techniques for neuroimaging have encouraged
scientists to implement models to diagnose brain disorders such as Alzheimer's disease at …

Transformers are becoming a core part of many neural network architectures, employed in a
wide range of applications such as NLP, Speech Recognition, Time Series, and Computer …

With the booming development of the online fashion industry, effective personalized
recommender systems have become indispensable for the convenience they brought to the …