Christoph Lohrmann

According to our database, Christoph Lohrmann authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

On the benefit of feature selection and ensemble feature selection for fuzzy k-nearest neighbor classification.

Christoph Lohrmann, Alena Lohrmann, Mahinda Mailagaha Kumbure

Appl. Soft Comput., 2025

2024

Emergence of chemotactic strategies with multi-agent reinforcement learning.

Samuel Tovey, Christoph Lohrmann, Christian Holm

Mach. Learn. Sci. Technol., 2024

SwarmRL: Building the Future of Smart Active Systems.

Samuel Tovey, Christoph Lohrmann, Tobias Merkt, David Zimmer, Konstantin Nikolaou, Simon Koppenhoefer, Anna Bushmakina, Jonas Scheunemann, Christian Holm

CoRR, 2024

2023

MDSuite: comprehensive post-processing tool for particle simulations.

Samuel Tovey, Fabian Zills, Francisco Torres-Herrador, Christoph Lohrmann, Marco Brückner, Christian Holm

J. Cheminformatics, December, 2023

Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning.

Samuel Tovey, David Zimmer, Christoph Lohrmann, Tobias Merkt, Simon Koppenhoefer, Veit-Lorenz Heuthe, Clemens Bechinger, Christian Holm

CoRR, 2023

2022

Machine learning techniques and data for stock market forecasting: A literature review.

Mahinda Mailagaha Kumbure, Christoph Lohrmann, Pasi Luukka, Jari Porras

Expert Syst. Appl., 2022

Nonspecificity, strife and total uncertainty in supervised feature selection.

Christoph Lohrmann, Pasi Luukka

Eng. Appl. Artif. Intell., 2022

2021

A Study on Relevant Features for Intraday S&P 500 Prediction Using a Hybrid Feature Selection Approach.

Mahinda Mailagaha Kumbure, Christoph Lohrmann, Pasi Luukka

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Image based classification of shipments using transfer learning.

Markus Leppioja, Pasi Luukka, Christoph Lohrmann

Proceedings of the Recent Advances in Business Analytics. Selected papers of the 2021 KNOWCON-NSAIS workshop on Business Analytics, 2021

2019

Using Clustering for Supervised Feature Selection to Detect Relevant Features.

Christoph Lohrmann, Pasi Luukka

Proceedings of the Machine Learning, Optimization, and Data Science, 2019

Information Transmission and Nonspecificity in Feature Selection.

Pasi Luukka, Christoph Lohrmann

Proceedings of the Fuzzy Techniques: Theory and Applications, 2019

2018

A combination of fuzzy similarity measures and fuzzy entropy measures for supervised feature selection.

Christoph Lohrmann, Pasi Luukka, Matylda Jablonska-Sabuka, Tuomo Kauranne

Expert Syst. Appl., 2018

A novel similarity classifier with multiple ideal vectors based on k-means clustering.

Christoph Lohrmann, Pasi Luukka

Decis. Support Syst., 2018