Markus Lange-Hegermann

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

20 Publikationen

Alle markieren

[20]
2024 | Konferenz - Poster | ELSA-ID: 11605
M. Trilling-Haasler, J. Tebbe, M. Lange-Hegermann, and J. 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
J. Tebbe, C. Zimmer, A. Steland, M. Lange-Hegermann, and F. Mies, Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. MLResearchPress , 2024, pp. 1333–1341.
ELSA | Download (ext.) | WoS
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
K. Y. Cheng, S. Pazmino, B. Bergh, M. Lange-Hegermann, and B. Schreiweis, An Image Retrieval Pipeline in a Medical Data Integration Center., vol. 310. IOS Press, Incorporated, 2024, pp. 1388–1389. doi: 10.3233/SHTI231208.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
K. Y. Cheng, M. Lange-Hegermann, J.-B. Hövener, and B. Schreiweis, “Instance-level medical image classification for text-based retrieval in a medical data integration center,” Computational and Structural Biotechnology Journal, vol. 24, pp. 434–450, 2024, doi: 10.1016/j.csbj.2024.06.006.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenz - Poster | ELSA-ID: 11381
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. Frahm, A systematic, model-based workflow for risk-based decision making in upstream development. DECHEMA e.V.
ELSA
 
[15]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
T. Hernández Rodriguez, C. Posch, R. Pörtner, M. Lange-Hegermann, F. M. Wurm, and B. 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
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. 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
M. Lange-Hegermann, T. Schmohl, A. Watanabe, K. Schelling, S. Heiss, and J. Rubart, KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer, vol. 4. Bielefeld: transcript Verlag, 2023, pp. 161–172. doi: 10.14361/9783839457696-009.
ELSA | DOI
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
H. Shayan, K. Krycki, M. Doemeland, and M. Lange-Hegermann, “PGNAA Spectral Classification of Metal With Density Estimations,” IEEE Transactions on Nuclear Science, vol. 70, no. 6, pp. 1171–1177, 2023, doi: 10.1109/tns.2023.3242626.
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
M. Härkönen, M. Lange-Hegermann, and B. Raiţă, Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients, vol. 202. MLResearchPress , 2023.
ELSA | WoS
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
J. Tebbe, T. Pawlik, M. Trilling-Haasler, J. Löbner, M. Lange-Hegermann, and J. Schneider, Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system. [Piscataway, NJ]: IEEE, 2023, pp. 1–7. doi: 10.1109/INDIN51400.2023.10217913.
ELSA | DOI | WoS
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. Frahm, “Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design,” Processes, vol. 10, no. 5, Art. no. 883, 2022, doi: 10.3390/pr10050883.
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. Frahm, A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. 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, vol. special issue, R. Pörtner and J. Möller, Eds. Basel: MDPI, 2022, pp. 21–48. doi: https://doi.org/10.3390/pr10050883.
ELSA | DOI
 
[6]
2022 | Konferenz - Poster | ELSA-ID: 10198
T. Hernández Rodriguez, R. Pörtner, M. Lange-Hegermann, F. M. Wurm, and B. 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
A. Besginow and M. Lange-Hegermann, Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations, vol. 35. Red Hook, NY : Curran Associates, Inc., 2022, pp. 29386–29399.
ELSA | WoS
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
M. Lange-Hegermann, T. Schmohl, A. Watanabe, S. Heiss, and J. Rubart, AI-based STEM education: Generating individualized exercises in mathematics, vol. 10. Bologna: Libreriauniversitaria.it, 2021, pp. 385–390.
ELSA | Download (ext.)
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
M. Lange-Hegermann, T. Schmohl, A. Watanabe, S. Heiss, and J. Rubart, AI-Based Stem Education: Generating Individualized Exercises in Mathematics. Bologna: Libreriauniversitaria.it, 2021, pp. 385–390.
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
M. Lange-Hegermann, Linearly Constrained Gaussian Processes with Boundary Conditions, vol. 130. MLResearchPress , 2021.
ELSA | WoS
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
F. Berns, M. Lange-Hegermann, and C. Beecks, Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. SCITEPRESS - Science and Technology Publications, 2020, pp. 87–92. doi: 10.5220/0010130300870092.
ELSA | DOI | WoS
 
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Zitationsstil: IEEE

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20 Publikationen

Alle markieren

[20]
2024 | Konferenz - Poster | ELSA-ID: 11605
M. Trilling-Haasler, J. Tebbe, M. Lange-Hegermann, and J. 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
J. Tebbe, C. Zimmer, A. Steland, M. Lange-Hegermann, and F. Mies, Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. MLResearchPress , 2024, pp. 1333–1341.
ELSA | Download (ext.) | WoS
 
[18]
2024 | Konferenz - Vortrag | ELSA-ID: 12816
K. Y. Cheng, S. Pazmino, B. Bergh, M. Lange-Hegermann, and B. Schreiweis, An Image Retrieval Pipeline in a Medical Data Integration Center., vol. 310. IOS Press, Incorporated, 2024, pp. 1388–1389. doi: 10.3233/SHTI231208.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[17]
2024 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12822
K. Y. Cheng, M. Lange-Hegermann, J.-B. Hövener, and B. Schreiweis, “Instance-level medical image classification for text-based retrieval in a medical data integration center,” Computational and Structural Biotechnology Journal, vol. 24, pp. 434–450, 2024, doi: 10.1016/j.csbj.2024.06.006.
ELSA | DOI | WoS | PubMed | Europe PMC
 
[16]
2023 | Konferenz - Poster | ELSA-ID: 11381
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. Frahm, A systematic, model-based workflow for risk-based decision making in upstream development. DECHEMA e.V.
ELSA
 
[15]
2023 | Konferenz - Vortrag | ELSA-ID: 11383
T. Hernández Rodriguez, C. Posch, R. Pörtner, M. Lange-Hegermann, F. M. Wurm, and B. 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
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. 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
M. Lange-Hegermann, T. Schmohl, A. Watanabe, K. Schelling, S. Heiss, and J. Rubart, KI-basierte Erstellung individualisierter Mathematikaufgaben für MINT-Fächer, vol. 4. Bielefeld: transcript Verlag, 2023, pp. 161–172. doi: 10.14361/9783839457696-009.
ELSA | DOI
 
[12]
2023 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 12811
H. Shayan, K. Krycki, M. Doemeland, and M. Lange-Hegermann, “PGNAA Spectral Classification of Metal With Density Estimations,” IEEE Transactions on Nuclear Science, vol. 70, no. 6, pp. 1171–1177, 2023, doi: 10.1109/tns.2023.3242626.
ELSA | DOI | WoS
 
[11]
2023 | Konferenzband - Beitrag | ELSA-ID: 12828
M. Härkönen, M. Lange-Hegermann, and B. Raiţă, Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients, vol. 202. MLResearchPress , 2023.
ELSA | WoS
 
[10]
2023 | Konferenzband - Beitrag | ELSA-ID: 10787
J. Tebbe, T. Pawlik, M. Trilling-Haasler, J. Löbner, M. Lange-Hegermann, and J. Schneider, Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system. [Piscataway, NJ]: IEEE, 2023, pp. 1–7. doi: 10.1109/INDIN51400.2023.10217913.
ELSA | DOI | WoS
 
[9]
2022 | Zeitschriftenaufsatz (wiss.) | ELSA-ID: 11377
T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. Frahm, “Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design,” Processes, vol. 10, no. 5, Art. no. 883, 2022, doi: 10.3390/pr10050883.
ELSA | DOI
 
[8]
2022 | Konferenz - Poster | ELSA-ID: 7932
T. Hernández Rodriguez, S. Ramm, M. Lange-Hegermann, and B. Frahm, A systematic, model-based workflow for risk-based decision making in upstream development.
ELSA
 
[7]
2022 | Sammelwerk - Beitrag | ELSA-ID: 10193
T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. 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, vol. special issue, R. Pörtner and J. Möller, Eds. Basel: MDPI, 2022, pp. 21–48. doi: https://doi.org/10.3390/pr10050883.
ELSA | DOI
 
[6]
2022 | Konferenz - Poster | ELSA-ID: 10198
T. Hernández Rodriguez, R. Pörtner, M. Lange-Hegermann, F. M. Wurm, and B. 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
A. Besginow and M. Lange-Hegermann, Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations, vol. 35. Red Hook, NY : Curran Associates, Inc., 2022, pp. 29386–29399.
ELSA | WoS
 
[4]
2021 | Konferenzband - Beitrag | ELSA-ID: 7581 | OA
M. Lange-Hegermann, T. Schmohl, A. Watanabe, S. Heiss, and J. Rubart, AI-based STEM education: Generating individualized exercises in mathematics, vol. 10. Bologna: Libreriauniversitaria.it, 2021, pp. 385–390.
ELSA | Download (ext.)
 
[3]
2021 | Konferenzband - Beitrag | ELSA-ID: 5620 | OA
M. Lange-Hegermann, T. Schmohl, A. Watanabe, S. Heiss, and J. Rubart, AI-Based Stem Education: Generating Individualized Exercises in Mathematics. Bologna: Libreriauniversitaria.it, 2021, pp. 385–390.
ELSA | DOI | Download (ext.)
 
[2]
2021 | Konferenzband - Beitrag | ELSA-ID: 12786
M. Lange-Hegermann, Linearly Constrained Gaussian Processes with Boundary Conditions, vol. 130. MLResearchPress , 2021.
ELSA | WoS
 
[1]
2020 | Konferenzband - Beitrag | ELSA-ID: 12812
F. Berns, M. Lange-Hegermann, and C. Beecks, Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. SCITEPRESS - Science and Technology Publications, 2020, pp. 87–92. doi: 10.5220/0010130300870092.
ELSA | DOI | WoS
 
Markierte Publikation(en)

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Publikationen filtern

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Zitationsstil: IEEE

Export / Einbettung