This survey presents a comprehensive overview of machine learning methods for
cybersecurity intrusion detection systems, with a specific focus on recent approaches based …

Abstract Internet of Things (IoT) and Artificial Intelligence (AI) play a vital role in the
upcoming years to improve the assistance systems. The IoT devices utilize several sensor …

As a deep learning model, a deep belief network (DBN) consists of multiple restricted
Boltzmann machines (RBMs). Based on DBN, many intelligent fault diagnosis methods are …

Abstract Training Restricted Boltzmann Machines (RBMs) has been challenging for a long
time due to the difficulty of computing precisely the log-likelihood gradient. Over the past …

Welding defect detection based on radiographic images plays a vital role in industrial
nondestructive testing. It provides an effective guarantee with respect to welding quality in …

It is well known that physical phenomena may be of great help in computing some difficult
problems efficiently. A typical example is prime factorization that may be solved in …

Classical probability distributions on sets of sequences can be modeled using quantum
states. Here, we do so with a quantum state that is pure and entangled. Because it is …

Constrained combinatorial optimization problems abound in industry, from portfolio
optimization to logistics. One of the major roadblocks in solving these problems is the …

Spiking Neural Networks (SNNs) claim to present many advantages in terms of biological
plausibility and energy efficiency compared to standard Deep Neural Networks (DNNs) …

Inspired by the possibility that generative models based on quantum circuits can provide a
useful inductive bias for sequence modeling tasks, we propose an efficient training algorithm …