Jan G. Rittig

According to our database, Jan G. Rittig authored at least 13 papers between 2022 and 2025.

Collaborative distances:

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

2025

Federated Learning from Molecules to Processes: A Perspective.

Jan G. Rittig, Clemens Kortmann

CoRR, June, 2025

Exploring data augmentation: Multi-task methods for molecular property prediction.

Muhammad bin Javaid, Timo Gervens, Alexander Mitsos, Martin Grohe, Jan G. Rittig

Comput. Chem. Eng., 2025

Predicting the temperature-dependent CMC of surfactant mixtures with graph neural networks.

Christoforos Brozos, Jan G. Rittig, Elie Akanny, Sandip Bhattacharya, Christina Kohlmann, Alexander Mitsos

Comput. Chem. Eng., 2025

2024

GraphXForm: Graph transformer for computer-aided molecular design with application to extraction.

Jonathan Pirnay, Jan G. Rittig, Alexander B. Wolf, Martin Grohe, Jakob Burger, Alexander Mitsos, Dominik G. Grimm

CoRR, 2024

Thermodynamics-Consistent Graph Neural Networks.

Jan G. Rittig, Alexander Mitsos

CoRR, 2024

Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks.

Christoforos Brozos, Jan G. Rittig, Sandip Bhattacharya, Elie Akanny, Christina Kohlmann, Alexander Mitsos

CoRR, 2024

Graph Neural Networks for Surfactant Multi-Property Prediction.

Christoforos Brozos, Jan G. Rittig, Sandip Bhattacharya, Elie Akanny, Christina Kohlmann, Alexander Mitsos

CoRR, 2024

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

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

Software for "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

Dataset, January, 2023

Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient Prediction.

Jan G. Rittig, Kobi C. Felton, Alexei A. Lapkin, Alexander Mitsos

CoRR, 2023

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