Manuel Dahmen

According to our database, Manuel Dahmen authored at least 21 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms.

Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis

SIAM J. Sci. Comput., 2024

Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimization.

Daniel Mayfrank, Na-Young Ahn, Alexander Mitsos, Manuel Dahmen

CoRR, 2024

2023

Demand response scheduling of copper production under short-term electricity price uncertainty.

Sonja H. M. Germscheid, Fritz T. C. Röben, Han Sun, André Bardow, Alexander Mitsos, Manuel Dahmen

Comput. Chem. Eng., October, 2023

Physical pooling functions in graph neural networks for molecular property prediction.

Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai Leonhard, Alexander Mitsos

Comput. Chem. Eng., April, 2023

Demand response for flat nonlinear MIMO processes using dynamic ramping constraints.

Florian Joseph Baader, Philipp Althaus, André Bardow, Manuel Dahmen

Comput. Chem. Eng., April, 2023

Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids.

Jan G. Rittig, Karim Ben Hicham, Artur M. Schweidtmann, Manuel Dahmen, Alexander Mitsos

Comput. Chem. Eng., March, 2023

Multivariate Scenario Generation of Day-Ahead Electricity Prices using Normalizing Flows.

Hannes Hilger, Dirk Witthaut, Manuel Dahmen, Leonardo Rydin Gorjão, Julius Trebbien, Eike Cramer

CoRR, 2023

End-to-End Reinforcement Learning of Koopman Models for Economic Nonlinear Model Predictive Control.

Daniel Mayfrank, Alexander Mitsos, Manuel Dahmen

CoRR, 2023

2022

Personalized Algorithm Generation: A Case Study in Learning ODE Integrators.

Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li

SIAM J. Sci. Comput., 2022

Graph neural networks for the prediction of molecular structure-property relationships.

Jan G. Rittig, Qinghe Gao, Manuel Dahmen, Alexander Mitsos, Artur M. Schweidtmann

CoRR, 2022

Graph Machine Learning for Design of High-Octane Fuels.

Jan G. Rittig, Martin Ritzert, Artur M. Schweidtmann, Stefanie Winkler, Jana M. Weber, Philipp Morsch, K. Alexander Heufer, Martin Grohe, Alexander Mitsos, Manuel Dahmen

CoRR, 2022

Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows.

Eike Cramer, Dirk Witthaut, Alexander Mitsos, Manuel Dahmen

CoRR, 2022

Nonlinear Isometric Manifold Learning for Injective Normalizing Flows.

Eike Cramer, Felix Rauh, Alexander Mitsos, Raúl Tempone, Manuel Dahmen

CoRR, 2022

Simultaneous optimization of design and operation of an air-cooled geothermal ORC under consideration of multiple operating points.

Marco Langiu, Manuel Dahmen, Alexander Mitsos

Comput. Chem. Eng., 2022

Normalizing flow-based day-ahead wind power scenario generation for profitable and reliable delivery commitments by wind farm operators.

Eike Cramer, Leonard Paeleke, Alexander Mitsos, Manuel Dahmen

Comput. Chem. Eng., 2022

Validation Methods for Energy Time Series Scenarios From Deep Generative Models.

Eike Cramer, Leonardo Rydin Gorjão, Alexander Mitsos, Benjamin Schäfer, Dirk Witthaut, Manuel Dahmen

IEEE Access, 2022

Incorporating AC Power Flow into the Multi-Energy System Optimization Framework COMANDO.

Philipp Glücker, Marco Langiu, Thiemo Pesch, Manuel Dahmen, Andrea Benigni

Proceedings of the Open Source Modelling and Simulation of Energy Systems, 2022

2021

Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators.

Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li

CoRR, 2021

Principal Component Density Estimation for Scenario Generation Using Normalizing Flows.

Eike Cramer, Alexander Mitsos, Raúl Tempone, Manuel Dahmen

CoRR, 2021

COMANDO: A Next-Generation Open-Source Framework for Energy Systems Optimization.

Marco Langiu, David Yang Shu, Florian Joseph Baader, Dominik Hering, Uwe Bau, André Xhonneux, Dirk Müller, André Bardow, Alexander Mitsos, Manuel Dahmen

Comput. Chem. Eng., 2021

2020

Integrated design of processes and products: Optimal renewable fuels.

Andrea König, Lisa Neidhardt, Jörn Viell, Alexander Mitsos, Manuel Dahmen

Comput. Chem. Eng., 2020