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, and Jan Schneider. Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast , 2024.
ELSA
 
[19]
2024 | Konferenzband - Beitrag | ELSA-ID: 12815 | OA
Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, and Fabian Mies. 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 , 2024.
ELSA | Download (ext.) | WoS
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann, and Bjorn Schreiweis. An Image Retrieval Pipeline in a Medical Data Integration Center. 19th World Congress on Medical and Health Informatics (MEDINFO). Vol. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated, 2024. https://doi.org/10.3233/SHTI231208.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener, and Björn Schreiweis. “Instance-Level Medical Image Classification for Text-Based Retrieval in a Medical Data Integration Center.” Computational and Structural Biotechnology Journal 24 (2024): 434–50. https://doi.org/10.1016/j.csbj.2024.06.006.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenz - Poster | ELSA-ID: 11381
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development. DECHEMA e.V., n.d.
ELSA
 
[15]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm, and Björn Frahm. Model-Assisted Design Strategies for Bioprocesses – Advanced Statistical Methods in Industrial Upstream Cell Culture. DECHEMA e.V., 2023.
ELSA
 
[14]
2023 | Konferenz - Poster | ELSA-ID: 10201 | OA
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development, 2023.
ELSA | Download (ext.)
 
[13]
2023 | Konferenzband - Beitrag | ELSA-ID: 9930
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Kathrin Schelling, Stefan Heiss, and Jessica Rubart. KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer. Edited by Tobias Schmohl, Alice Watanabe, and Kathrin Schelling. Künstliche Intelligenz in der Hochschulbildung: Chancen und Grenzen des KI-gestützten Lernens und Lehrens. Vol. 4. Hochschulbildung: Lehre und Forschung. Bielefeld: transcript Verlag, 2023. https://doi.org/10.14361/9783839457696-009.
ELSA | DOI
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
Shayan, Helmand, Kai Krycki, Marco Doemeland, and Markus Lange-Hegermann. “PGNAA Spectral Classification of Metal With Density Estimations.” IEEE Transactions on Nuclear Science 70, no. 6 (2023): 1171–77. https://doi.org/10.1109/tns.2023.3242626.
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
Härkönen, Marc , Markus Lange-Hegermann, and Bogdan Raiţă. Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients. 40th International Conference on Machine Learning. Vol. 202. Proceedings of Machine Learning Research : PMLR. MLResearchPress , 2023.
ELSA | WoS
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
Tebbe, Jörn, Thomas Pawlik, Marc Trilling-Haasler, Jannis Löbner, Markus Lange-Hegermann, and Jan Schneider. Holistic Optimization of a Dynamic Cross-Flow Filtration Process towards a Cyber-Physical System. Edited by Jürgen Jasperneite, Lukasz Wisniewski, Kim Fung Man, and Institute of Electrical and Electronics Engineers . 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE, 2023. https://doi.org/10.1109/INDIN51400.2023.10217913.
ELSA | DOI | WoS
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and Björn Frahm. “Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.” Processes 10, no. 5 (2022). https://doi.org/10.3390/pr10050883.
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development, n.d.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and Björn Frahm. “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, edited by Ralf Pörtner and Johannes Möller, special issue:21–48. Processes : Open Access Journal. Basel: MDPI, 2022. 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, and Björn Frahm. A Systematic, Model-Based Approach for Decision Making in Upstream Development – Considerations Regarding Clone Selection and Cell Expansion, n.d.
ELSA
 
[5]
2022 | Konferenzband - Beitrag | ELSA-ID: 12804
Besginow, Andreas, and Markus Lange-Hegermann. Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations. Edited by S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh, and Neural Information Processing Systems Foundation . 36th Conference on Neural Information Processing Systems (NeurIPS 2022) . Vol. 35. Advances in Neural Information Processing Systems. Red Hook, NY : Curran Associates, Inc., 2022.
ELSA | WoS
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss, and Jessica Rubart. AI-Based STEM Education: Generating Individualized Exercises in Mathematics. New Perspectives in Science Education. Vol. 10. Bologna: Libreriauniversitaria.it, 2021.
ELSA | Download (ext.)
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss, and Jessica Rubart. 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, 2021. https://doi.org/10.26352/F318_2384-9509.
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
Lange-Hegermann, Markus. Linearly Constrained Gaussian Processes with Boundary Conditions. Edited by A. Banerjee and K. Fukumizu. 24th International Conference on Artificial Intelligence and Statistics (AISTATS). Vol. 130. Proceedings of Machine Learning Research : PMLR . MLResearchPress , 2021.
ELSA | WoS
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
Berns, Fabian, Markus Lange-Hegermann, and Christian Beecks. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Edited by H. Panetto, K. Madani, and A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications, 2020. https://doi.org/10.5220/0010130300870092.
ELSA | DOI | WoS
 
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Zitationsstil: Chicago (en)

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20 Publikationen

Alle markieren

[20]
2024 | Konferenz - Poster | ELSA-ID: 11605
Trilling-Haasler, Marc, Jörn Tebbe, Markus Lange-Hegermann, and Jan Schneider. Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast , 2024.
ELSA
 
[19]
2024 | Konferenzband - Beitrag | ELSA-ID: 12815 | OA
Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, and Fabian Mies. 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 , 2024.
ELSA | Download (ext.) | WoS
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann, and Bjorn Schreiweis. An Image Retrieval Pipeline in a Medical Data Integration Center. 19th World Congress on Medical and Health Informatics (MEDINFO). Vol. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated, 2024. https://doi.org/10.3233/SHTI231208.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener, and Björn Schreiweis. “Instance-Level Medical Image Classification for Text-Based Retrieval in a Medical Data Integration Center.” Computational and Structural Biotechnology Journal 24 (2024): 434–50. https://doi.org/10.1016/j.csbj.2024.06.006.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenz - Poster | ELSA-ID: 11381
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development. DECHEMA e.V., n.d.
ELSA
 
[15]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner, Markus Lange-Hegermann, Florian M. Wurm, and Björn Frahm. Model-Assisted Design Strategies for Bioprocesses – Advanced Statistical Methods in Industrial Upstream Cell Culture. DECHEMA e.V., 2023.
ELSA
 
[14]
2023 | Konferenz - Poster | ELSA-ID: 10201 | OA
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development, 2023.
ELSA | Download (ext.)
 
[13]
2023 | Konferenzband - Beitrag | ELSA-ID: 9930
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Kathrin Schelling, Stefan Heiss, and Jessica Rubart. KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer. Edited by Tobias Schmohl, Alice Watanabe, and Kathrin Schelling. Künstliche Intelligenz in der Hochschulbildung: Chancen und Grenzen des KI-gestützten Lernens und Lehrens. Vol. 4. Hochschulbildung: Lehre und Forschung. Bielefeld: transcript Verlag, 2023. https://doi.org/10.14361/9783839457696-009.
ELSA | DOI
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
Shayan, Helmand, Kai Krycki, Marco Doemeland, and Markus Lange-Hegermann. “PGNAA Spectral Classification of Metal With Density Estimations.” IEEE Transactions on Nuclear Science 70, no. 6 (2023): 1171–77. https://doi.org/10.1109/tns.2023.3242626.
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
Härkönen, Marc , Markus Lange-Hegermann, and Bogdan Raiţă. Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients. 40th International Conference on Machine Learning. Vol. 202. Proceedings of Machine Learning Research : PMLR. MLResearchPress , 2023.
ELSA | WoS
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
Tebbe, Jörn, Thomas Pawlik, Marc Trilling-Haasler, Jannis Löbner, Markus Lange-Hegermann, and Jan Schneider. Holistic Optimization of a Dynamic Cross-Flow Filtration Process towards a Cyber-Physical System. Edited by Jürgen Jasperneite, Lukasz Wisniewski, Kim Fung Man, and Institute of Electrical and Electronics Engineers . 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). [Piscataway, NJ]: IEEE, 2023. https://doi.org/10.1109/INDIN51400.2023.10217913.
ELSA | DOI | WoS
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and Björn Frahm. “Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.” Processes 10, no. 5 (2022). https://doi.org/10.3390/pr10050883.
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
Hernández Rodriguez, Tanja, Selina Ramm, Markus Lange-Hegermann, and Björn Frahm. A Systematic, Model-Based Workflow for Risk-Based Decision Making in Upstream Development, n.d.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and Björn Frahm. “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, edited by Ralf Pörtner and Johannes Möller, special issue:21–48. Processes : Open Access Journal. Basel: MDPI, 2022. 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, and Björn Frahm. A Systematic, Model-Based Approach for Decision Making in Upstream Development – Considerations Regarding Clone Selection and Cell Expansion, n.d.
ELSA
 
[5]
2022 | Konferenzband - Beitrag | ELSA-ID: 12804
Besginow, Andreas, and Markus Lange-Hegermann. Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations. Edited by S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh, and Neural Information Processing Systems Foundation . 36th Conference on Neural Information Processing Systems (NeurIPS 2022) . Vol. 35. Advances in Neural Information Processing Systems. Red Hook, NY : Curran Associates, Inc., 2022.
ELSA | WoS
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss, and Jessica Rubart. AI-Based STEM Education: Generating Individualized Exercises in Mathematics. New Perspectives in Science Education. Vol. 10. Bologna: Libreriauniversitaria.it, 2021.
ELSA | Download (ext.)
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
Lange-Hegermann, Markus, Tobias Schmohl, Alice Watanabe, Stefan Heiss, and Jessica Rubart. 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, 2021. https://doi.org/10.26352/F318_2384-9509.
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
Lange-Hegermann, Markus. Linearly Constrained Gaussian Processes with Boundary Conditions. Edited by A. Banerjee and K. Fukumizu. 24th International Conference on Artificial Intelligence and Statistics (AISTATS). Vol. 130. Proceedings of Machine Learning Research : PMLR . MLResearchPress , 2021.
ELSA | WoS
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
Berns, Fabian, Markus Lange-Hegermann, and Christian Beecks. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Edited by H. Panetto, K. Madani, and A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications, 2020. https://doi.org/10.5220/0010130300870092.
ELSA | DOI | WoS
 
Markierte Publikation(en)

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: Chicago (en)

Export / Einbettung