20 Publikationen
    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.
    
    
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    2024 |  Konferenzband - Beitrag | ELSA-ID: 12815 | 
    
    
      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
  
  
  
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    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
  
  
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   | PubMed | Europe PMC
  
  
  
  
    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.
    
    
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   | WoS
   | PubMed | Europe PMC
  
  
  
  
    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.
    
    
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    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.
    
    
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    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.
    
    
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    2023 |  Konferenz - Poster | ELSA-ID: 10201 | 
    
    
      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.
    
    
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    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.
    
    
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    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.
    
    
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   | WoS
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    2021 |  Konferenzband - Beitrag | ELSA-ID: 7581 | 
    
    
      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
  
  
  
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    2021 |  Konferenzband - Beitrag | ELSA-ID: 5620 | 
    
    
      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
  
  
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   | Download (ext.)
  
  
  
  
  
  
    2021 |  Konferenzband - Beitrag | ELSA-ID: 12786 
    
      M. Lange-Hegermann, Linearly Constrained Gaussian Processes with Boundary Conditions, vol. 130. MLResearchPress , 2021.
    
    
ELSA
  
  
  
  
  
  
  
  
  
  
    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.
    
    
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20 Publikationen
    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
  
  
  
  
  
  
  
  
  
  
    2024 |  Konferenzband - Beitrag | ELSA-ID: 12815 | 
    
    
      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.)
  
  
  
  
  
  
    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
  
  
   | PubMed | Europe PMC
  
  
  
  
    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
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    2023 |  Konferenz - Poster | ELSA-ID: 10201 | 
    
    
      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.)
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    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
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    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
  
  
  
  
  
  
  
  
  
  
    2021 |  Konferenzband - Beitrag | ELSA-ID: 7581 | 
    
    
      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.)
  
  
  
  
  
  
    2021 |  Konferenzband - Beitrag | ELSA-ID: 5620 | 
    
    
      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.)
  
  
  
  
  
  
    2021 |  Konferenzband - Beitrag | ELSA-ID: 12786 
    
      M. Lange-Hegermann, Linearly Constrained Gaussian Processes with Boundary Conditions, vol. 130. MLResearchPress , 2021.
    
    
ELSA
  
  
  
  
  
  
  
  
  
  
    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