Markus Lange-Hegermann

markus.lange-hegermann@th-owl.de
ID
71761

20 Publikationen

Alle markieren

[20]
2024 | Konferenz - Poster | ELSA-ID: 11605
Trilling-Haasler, Marc, Jörn Tebbe, Markus Lange-Hegermann und Jan Schneider. 2024. Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast .
ELSA
 
[19]
2024 | Konferenzband - Beitrag | ELSA-ID: 12815 | OA
Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann und Fabian Mies. 2024. Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238. Proceedings of Machine Learning Research. MLResearchPress .
ELSA | Download (ext.)
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann und Bjorn Schreiweis. 2024. An Image Retrieval Pipeline in a Medical Data Integration Center. 19th World Congress on Medical and Health Informatics (MEDINFO). Bd. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated. doi:10.3233/SHTI231208, .
ELSA | DOI | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener und Björn Schreiweis. 2024. Instance-level medical image classification for text-based retrieval in a medical data integration center. Computational and Structural Biotechnology Journal 24: 434–450. doi:10.1016/j.csbj.2024.06.006, .
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
Tebbe, Jörn, Thomas Pawlik, Marc Trilling-Haasler, Jannis Löbner, Markus Lange-Hegermann und Jan Schneider. 2023. Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system. Hg. von Jürgen Jasperneite, Lukasz Wisniewski, Kim Fung Man, und Institute of Electrical and Electronics Engineers . 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE. doi:10.1109/INDIN51400.2023.10217913, .
ELSA | DOI
 
[15]
2023 | Konferenz - Poster | ELSA-ID: 11381
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. A systematic, model-based workflow for risk-based decision making in upstream development. DECHEMA e.V.
ELSA
 
[14]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm und Björn Frahm. 2023. Model-assisted design strategies for bioprocesses – Advanced statistical methods in industrial upstream cell culture. DECHEMA e.V.
ELSA
 
[13]
2023 | Konferenz - Poster | ELSA-ID: 10201 | OA
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. 2023. A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA | Download (ext.)
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
Shayan, Helmand, Kai Krycki, Marco Doemeland und Markus Lange-Hegermann. 2023. PGNAA Spectral Classification of Metal With Density Estimations. IEEE Transactions on Nuclear Science 70, Nr. 6: 1171–1177. doi:10.1109/tns.2023.3242626, .
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
Härkönen, Marc , Markus Lange-Hegermann und Bogdan Raiţă. 2023. Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients. 40th International Conference on Machine Learning. Bd. 202. Proceedings of machine learning research : PMLR. MLResearchPress .
ELSA
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 9930
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Kathrin Schelling, Stefan Heiss und Jessica Rubart. 2023. KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer. Hg. von Tobias Schmohl, Alice Watanabe, und Kathrin Schelling. Künstliche Intelligenz in der Hochschulbildung: Chancen und Grenzen des KI-gestützten Lernens und Lehrens. Bd. 4. Hochschulbildung: Lehre und Forschung. Bielefeld: transcript Verlag. doi:10.14361/9783839457696-009, .
ELSA | DOI
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und Björn Frahm. 2022. Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design. Processes 10, Nr. 5. doi:10.3390/pr10050883, .
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und Björn Frahm. 2022. Designing robust biotechnological processes regarding variabilities using multi-objective optimization applied to a biopharmaceutical seed train design. In: Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing, hg. von Ralf Pörtner und Johannes Möller, special issue:21–48. Processes : open access journal. Basel: MDPI. doi:https://doi.org/10.3390/pr10050883, .
ELSA | DOI
 
[6]
2022 | Konferenz - Poster | ELSA-ID: 10198
Hernández Rodriguez, Tanja, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm und Björn Frahm. A systematic, model-based approach for decision making in upstream development – Considerations regarding clone selection and cell expansion.
ELSA
 
[5]
2022 | Konferenzband - Beitrag | ELSA-ID: 12804
Besginow, Andreas und Markus Lange-Hegermann. 2022. Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations. Hg. von S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh, und Neural Information Processing Systems Foundation . 36th Conference on Neural Information Processing Systems (NeurIPS 2022) . Bd. 35. Advances in Neural Information Processing Systems. Red Hook, NY : Curran Associates, Inc.
ELSA
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
Lange-Hegermann, Markus. 2021. Linearly Constrained Gaussian Processes with Boundary Conditions. Hg. von A. Banerjee und K. Fukumizu. 24th International Conference on Artificial Intelligence and Statistics (AISTATS). Bd. 130. Proceedings of machine learning research : PMLR . MLResearchPress .
ELSA
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss und Jessica Rubart. 2021. AI-Based Stem Education: Generating Individualized Exercises in Mathematics. New Perspectives in Science Education. Filodiritto Editore – 10th International Conference New Perspectives in Science Education. Bologna: Libreriauniversitaria.it. doi:10.26352/F318_2384-9509, .
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss und Jessica Rubart. 2021. AI-based STEM education: Generating individualized exercises in mathematics. New Perspectives in Science Education. Bd. 10. Bologna: Libreriauniversitaria.it.
ELSA | Download (ext.)
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
Berns, Fabian, Markus Lange-Hegermann und Christian Beecks. 2020. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Hg. von H. Panetto, K. Madani, und A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010130300870092, .
ELSA | DOI
 
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Zitationsstil: Chicago (de)

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20 Publikationen

Alle markieren

[20]
2024 | Konferenz - Poster | ELSA-ID: 11605
Trilling-Haasler, Marc, Jörn Tebbe, Markus Lange-Hegermann und Jan Schneider. 2024. Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast .
ELSA
 
[19]
2024 | Konferenzband - Beitrag | ELSA-ID: 12815 | OA
Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann und Fabian Mies. 2024. Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238. Proceedings of Machine Learning Research. MLResearchPress .
ELSA | Download (ext.)
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann und Bjorn Schreiweis. 2024. An Image Retrieval Pipeline in a Medical Data Integration Center. 19th World Congress on Medical and Health Informatics (MEDINFO). Bd. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated. doi:10.3233/SHTI231208, .
ELSA | DOI | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener und Björn Schreiweis. 2024. Instance-level medical image classification for text-based retrieval in a medical data integration center. Computational and Structural Biotechnology Journal 24: 434–450. doi:10.1016/j.csbj.2024.06.006, .
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
Tebbe, Jörn, Thomas Pawlik, Marc Trilling-Haasler, Jannis Löbner, Markus Lange-Hegermann und Jan Schneider. 2023. Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system. Hg. von Jürgen Jasperneite, Lukasz Wisniewski, Kim Fung Man, und Institute of Electrical and Electronics Engineers . 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE. doi:10.1109/INDIN51400.2023.10217913, .
ELSA | DOI
 
[15]
2023 | Konferenz - Poster | ELSA-ID: 11381
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. A systematic, model-based workflow for risk-based decision making in upstream development. DECHEMA e.V.
ELSA
 
[14]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm und Björn Frahm. 2023. Model-assisted design strategies for bioprocesses – Advanced statistical methods in industrial upstream cell culture. DECHEMA e.V.
ELSA
 
[13]
2023 | Konferenz - Poster | ELSA-ID: 10201 | OA
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. 2023. A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA | Download (ext.)
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
Shayan, Helmand, Kai Krycki, Marco Doemeland und Markus Lange-Hegermann. 2023. PGNAA Spectral Classification of Metal With Density Estimations. IEEE Transactions on Nuclear Science 70, Nr. 6: 1171–1177. doi:10.1109/tns.2023.3242626, .
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
Härkönen, Marc , Markus Lange-Hegermann und Bogdan Raiţă. 2023. Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients. 40th International Conference on Machine Learning. Bd. 202. Proceedings of machine learning research : PMLR. MLResearchPress .
ELSA
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 9930
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Kathrin Schelling, Stefan Heiss und Jessica Rubart. 2023. KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer. Hg. von Tobias Schmohl, Alice Watanabe, und Kathrin Schelling. Künstliche Intelligenz in der Hochschulbildung: Chancen und Grenzen des KI-gestützten Lernens und Lehrens. Bd. 4. Hochschulbildung: Lehre und Forschung. Bielefeld: transcript Verlag. doi:10.14361/9783839457696-009, .
ELSA | DOI
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und Björn Frahm. 2022. Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design. Processes 10, Nr. 5. doi:10.3390/pr10050883, .
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann und Björn Frahm. A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und Björn Frahm. 2022. Designing robust biotechnological processes regarding variabilities using multi-objective optimization applied to a biopharmaceutical seed train design. In: Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing, hg. von Ralf Pörtner und Johannes Möller, special issue:21–48. Processes : open access journal. Basel: MDPI. doi:https://doi.org/10.3390/pr10050883, .
ELSA | DOI
 
[6]
2022 | Konferenz - Poster | ELSA-ID: 10198
Hernández Rodriguez, Tanja, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm und Björn Frahm. A systematic, model-based approach for decision making in upstream development – Considerations regarding clone selection and cell expansion.
ELSA
 
[5]
2022 | Konferenzband - Beitrag | ELSA-ID: 12804
Besginow, Andreas und Markus Lange-Hegermann. 2022. Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations. Hg. von S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh, und Neural Information Processing Systems Foundation . 36th Conference on Neural Information Processing Systems (NeurIPS 2022) . Bd. 35. Advances in Neural Information Processing Systems. Red Hook, NY : Curran Associates, Inc.
ELSA
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
Lange-Hegermann, Markus. 2021. Linearly Constrained Gaussian Processes with Boundary Conditions. Hg. von A. Banerjee und K. Fukumizu. 24th International Conference on Artificial Intelligence and Statistics (AISTATS). Bd. 130. Proceedings of machine learning research : PMLR . MLResearchPress .
ELSA
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss und Jessica Rubart. 2021. AI-Based Stem Education: Generating Individualized Exercises in Mathematics. New Perspectives in Science Education. Filodiritto Editore – 10th International Conference New Perspectives in Science Education. Bologna: Libreriauniversitaria.it. doi:10.26352/F318_2384-9509, .
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss und Jessica Rubart. 2021. AI-based STEM education: Generating individualized exercises in mathematics. New Perspectives in Science Education. Bd. 10. Bologna: Libreriauniversitaria.it.
ELSA | Download (ext.)
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
Berns, Fabian, Markus Lange-Hegermann und Christian Beecks. 2020. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Hg. von H. Panetto, K. Madani, und A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010130300870092, .
ELSA | DOI
 
Markierte Publikation(en)

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Publikationen filtern

Darstellung / Sortierung

Zitationsstil: Chicago (de)

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