research
∙
05/09/2023
Pseudo-Hamiltonian system identification
Identifying the underlying dynamics of physical systems can be challengi...
share
research
∙
03/03/2023
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks
Deep neural networks are an attractive alternative for simulating comple...
research
∙
06/06/2022
Port-Hamiltonian Neural Networks with State Dependent Ports
Hybrid machine learning based on Hamiltonian formulations has recently b...
research
∙
03/31/2022
Mutual information estimation for graph convolutional neural networks
Measuring model performance is a key issue for deep learning practitione...
research
∙
09/02/2021
Inferring feature importance with uncertainties in high-dimensional data
Estimating feature importance is a significant aspect of explaining data...
research
∙
12/09/2020
Deep Reinforcement Learning for Long Term Hydropower Production Scheduling
We explore the use of deep reinforcement learning to provide strategies ...
research
∙
03/10/2020
Improved VIV response prediction using adaptive parameters and data clustering
Slender marine structures such as deep-water riser systems are continuou...
research
∙
06/24/2019