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09/18/2023
Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions
With the recent wave of digitalization, specifically in the context of s...
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09/18/2023
Machine Learning for enhancing Wind Field Resolution in Complex Terrain
Atmospheric flows are governed by a broad variety of spatio-temporal sca...
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07/01/2023
CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis
Generative adversarial networks (GANs) have drawn considerable attention...
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02/24/2023
Deep active learning for nonlinear system identification
The exploding research interest for neural networks in modeling nonlinea...
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01/02/2023
Sparse neural networks with skip-connections for nonlinear system identification
Data-driven models such as neural networks are being applied more and mo...
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12/14/2022
Artificial intelligence-driven digital twin of a modern house demonstrated in virtual reality
A digital twin is a powerful tool that can help monitor and optimize phy...
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09/22/2022
A novel corrective-source term approach to modeling unknown physics in aluminum extraction process
With the ever-increasing availability of data, there has been an explosi...
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09/13/2022
Sparse deep neural networks for modeling aluminum electrolysis dynamics
Artificial neural networks have a broad array of applications today due ...
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08/15/2022
Prospects of federated machine learning in fluid dynamics
Physics-based models have been mainstream in fluid dynamics for developi...
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06/07/2022
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
Upcoming technologies like digital twins, autonomous, and artificial int...
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05/25/2022
Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling
We propose a new physics guided machine learning (PGML) paradigm that le...
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05/13/2022
Physics guided neural networks for modelling of non-linear dynamics
The success of the current wave of artificial intelligence can be partly...
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02/02/2022
Data Processing Framework for Ship Performance Analysis
The hydrodynamic performance of a sea-going ship can be analysed using t...
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10/15/2021
Nonlinear proper orthogonal decomposition for convection-dominated flows
Autoencoder techniques find increasingly common use in reduced order mod...
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10/07/2021
Ship Performance Monitoring using Machine-learning
The hydrodynamic performance of a sea-going ship varies over its lifespa...
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05/24/2021
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
Hybrid Analysis and Modeling (HAM) is an emerging modeling paradigm whic...
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03/26/2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
Most modeling approaches lie in either of the two categories: physics-ba...
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03/15/2021
Geometric Change Detection in Digital Twins using 3D Machine Learning
Digital twins are meant to bridge the gap between real-world physical sy...
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12/22/2020
On the effectiveness of signal decomposition, feature extraction and selection on lung sound classification
Lung sounds refer to the sound generated by air moving through the respi...
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08/05/2020
A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction
We put forth a long short-term memory (LSTM) nudging framework for the e...
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06/17/2020
Interface learning of multiphysics and multiscale systems
Complex natural or engineered systems comprise multiple characteristic s...
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06/17/2020
Deep Reinforcement Learning Controller for 3D Path-following and Collision Avoidance by Autonomous Underwater Vehicles
Control theory provides engineers with a multitude of tools to design co...
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06/16/2020
COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle using Deep Reinforcement Learning
Path Following and Collision Avoidance, be it for unmanned surface vesse...
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02/03/2020
Proportional integral derivative controller assisted reinforcement learning for path following by autonomous underwater vehicles
Control theory provides engineers with a multitude of tools to design co...
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12/18/2019
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
In this article, we explore the feasibility of applying proximal policy ...
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10/09/2019
Dissecting Deep Neural Networks
In exchange for large quantities of data and processing power, deep neur...
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06/24/2019
