To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by York University has found that not only could machine-learning models ...

Abstract: Spatial dependency modeling, with the objective of uncovering the intricate spatial correlations within spatiotemporal data, plays a crucial role in traffic forecasting. Current research ...

Data exploration, usually the first step in data analysis, is a useful method to tackle challenges caused by big geoscience data. It conducts quick analysis of data, investigates the patterns, and ...

Fullerenes are hollow carbon molecules where each atom is connected to exactly three other atoms, arranged in pentagonal and hexagonal rings. Mathematically, they can be combinatorially modeled as ...

Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional ...

The concept of a swarm of drones assumes the presence of a wireless ad hoc network, in which drones are network nodes and exchanging information with each other. This article is devoted to studying ...

Intuition plays a crucial role in human driving decision-making, and this rapid and unconscious cognitive process is essential for improving traffic safety. We used the first proposed multi-layer ...

Quantum computing is a novel computational paradigm that harnesses the fundamental principles of quantum mechanics to perform calculations. In comparison to classical computers, quantum computers can ...