Data-driven prediction in dynamical systems: recent developments
In recent years, we have witnessed a significant shift toward ever-more complex and ever-
larger-scale systems in the majority of the grand societal challenges tackled in applied …
larger-scale systems in the majority of the grand societal challenges tackled in applied …
[HTML][HTML] Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion
Deep learning (DL) in orthopaedics has gained significant attention in recent years.
Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks …
Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks …
[HTML][HTML] A new family of Constitutive Artificial Neural Networks towards automated model discovery
For more than 100 years, chemical, physical, and material scientists have proposed
competing constitutive models to best characterize the behavior of natural and man-made …
competing constitutive models to best characterize the behavior of natural and man-made …
Bayesian Physics Informed Neural Networks for real-world nonlinear dynamical systems
Understanding real-world dynamical phenomena remains a challenging task. Across
various scientific disciplines, machine learning has advanced as the go-to technology to …
various scientific disciplines, machine learning has advanced as the go-to technology to …
Automated model discovery for human brain using constitutive artificial neural networks
The brain is our softest and most vulnerable organ, and understanding its physics is a
challenging but significant task. Throughout the past decade, numerous competing models …
challenging but significant task. Throughout the past decade, numerous competing models …
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation
Infectious disease modelling can serve as a powerful tool for situational awareness and
decision support for policy makers. However, COVID-19 modelling efforts faced many …
decision support for policy makers. However, COVID-19 modelling efforts faced many …
What Drives People's Willingness to Adopt Autonomous Vehicles? A Review of Internal and External Factors
This article presents a state-of-the-art literature review to understand people's perceptions
and opinions of Autonomous Vehicles and the factors that influence their adoption. A …
and opinions of Autonomous Vehicles and the factors that influence their adoption. A …
[HTML][HTML] Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations
Our recent study has found that physics-informed neural networks (PINN) tend to be local
approximators after training. This observation led to the development of a novel physics …
approximators after training. This observation led to the development of a novel physics …
Global and local mobility as a barometer for COVID-19 dynamics
The spreading of infectious diseases including COVID-19 depends on human interactions.
In an environment where behavioral patterns and physical contacts are constantly evolving …
In an environment where behavioral patterns and physical contacts are constantly evolving …
Real-time COVID-19 forecasting: challenges and opportunities of model performance and translation
The COVID-19 pandemic brought mathematical modelling into the spotlight, as scientists
rushed to use data to understand transmission patterns and disease severity, and to …
rushed to use data to understand transmission patterns and disease severity, and to …