research
∙
09/11/2023
Data-Driven Model Reduction and Nonlinear Model Predictive Control of an Air Separation Unit by Applied Koopman Theory
Achieving real-time capability is an essential prerequisite for the indu...
share
research
∙
08/31/2023
Data-driven Product-Process Optimization of N-isopropylacrylamide Microgel Flow-Synthesis
Microgels are cross-linked, colloidal polymer networks with great potent...
research
∙
08/03/2023
End-to-End Reinforcement Learning of Koopman Models for Economic Nonlinear MPC
(Economic) nonlinear model predictive control ((e)NMPC) requires dynamic...
research
∙
11/22/2022
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
Meta-learning of numerical algorithms for a given task consist of the da...
research
∙
07/27/2022
Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction
Graph neural networks (GNNs) are emerging in chemical engineering for th...
research
∙
06/23/2022
Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids
Ionic liquids (ILs) are important solvents for sustainable processes and...
research
∙
06/01/2022
Graph Machine Learning for Design of High-Octane Fuels
Fuels with high-knock resistance enable modern spark-ignition engines to...
research
∙
05/27/2022
Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows
Electricity is traded on various markets with different time horizons an...
research
∙
04/05/2022
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators
We present a specialized scenario generation method that utilizes foreca...
research
∙
03/08/2022
Nonlinear Isometric Manifold Learning for Injective Normalizing Flows
To model manifold data using normalizing flows, we propose to employ the...
research
∙
10/27/2021
Validation Methods for Energy Time Series Scenarios from Deep Generative Models
The design and operation of modern energy systems are heavily influenced...
research
∙
04/21/2021
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows
Neural networks-based learning of the distribution of non-dispatchable r...
research
∙
02/07/2021
Design of Dynamic Experiments for Black-Box Model Discrimination
Diverse domains of science and engineering require and use mechanistic m...
research
∙
05/21/2020
