Sommer 2022
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Courses
2022 Data Management for End-to-End Machine Learning
The comprehensive analysis of large volumes of data is crucial in modern information systems.
Some of the main driving forces are current trends such as Industrie 4.0 and the Internet of Things (IoT).
In particular, applying machine learning (ML) to data of real-world scenarios imposes various data management
challenges in several steps of an end-to-end ML application.
Very often, the characteristics of real-world data impose challenges themselves.
For instance, data may change over time (data set shifts in non-stationary environments).
Here, major problems are how to detect and characterize these changes (e.g., different concept drifts),
as well as how to consider them in adaptive machine learning strategies.
Furthermore, organizations typically train a multitude of machine learning models from their data.
These ML models and their lifecycle have to be managed in a comprehensive way.
Afterwards, the most suitable models have to be selected for a concrete application,
e.g., via approaches to model discovery or AutoML. Moreover, many machine learning models
provide some kind of prediction. Here, it is mandatory for the users to understand why a
certain prediction was provided by the model. Finding methods to offer such explanations and
thus to help people interpret the models correctly, instead of treating them just as black boxes,
is another important challenge. In this seminar, we address current technologies, concepts,
algorithms and system infrastructures for above-mentioned challenges for data management
in end-to-end machine learning, for example:
• Machine learning with complex data characteristics, e.g., in non-stationary environments
• Comprehensive management of machine learning models
• Automatic selection of machine learning models (e.g., AutoML, Meta-Learning)
• Explainable artificial intelligence / interpretable machine learning
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Additive Fertigungsverfahren
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Advanced Finite Element Technology
Dr.-Ing. M. von Scheven and Prof. Dr.-Ing. habil. M. Bischoff
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Advanced Simulation Methods
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Algorithmische Gruppentheorie [Vorlesung]
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Analysis 2
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Analysis 2 (Gruppenübungen)
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Analytical Methods for Heat Transfer and Fluid Flow Problems
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Analytische und Numerische Methoden
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Analyzing Software using Deep Learning
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Antikörper Engineering
Vorlesung zu Antikörper Engineering im Masterstudiengang Technische Biologie, als Teil des Spezialisierungsmoduls. Kann auch als Vertiefende Vorlesung gehört und geprüft werden.
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Antikörper-Engineering [Seminar]
Seminar verpflichtend für alle Teilnehmer des Spezialisierungsmoduls Antikörper Engineering
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Antikörper-Engineering [Übung]
Übungen im Rahmen des Spezialisierungsmoduls Antikörper Engineering
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Astrophysik II MSc
Inhaltsverzeichnis
Mit dieser Vorlesung wird die im Wintersemester 2020/21 begonnene Vorlesung zum Wahlpflichtfach Astronomie und Astrophysik fortgesetzt. Es handelt sich nicht um einen Grundkurs in Astronomie, vielmehr stehen die physikalischen und vor allem die theoretisch-physikalischen Grundlagen, die in der traditionellen und der modernen Astrophysik für das Verständnis der Vorgänge im Kosmos von Bedeutung sind, im Vordergrund.
Die Themen sind:
Kosmologie auf der Grundlage der Allgemeinen Relativitätstheorie Lösung der Gravitationsgleichungen, kosmologische Rotverschiebung, Weltmodelle mit kosmologischer Konstante)
Supernovae und Kosmologie (Abschätzung des Zustands des Universums)
Das frühe Universum (Szenarien für die Evolution des Universums)
Literaturverzeichnis
Boblest, Müller, Wunner: Spezielle und Allgemeine Relativitätstheorie - Grundlagen, Anwendungen in Astrophysik und Kosmologie sowie relativistische Visualisierung (Springer, 2015), elektronische Ausgabe
Weigert, Wendker: Astronomie und Astrophysik, VCH Verlagsgesellschaft (1996)
Rebhan: Theoretische Physik Band 1 ... Relativitätstheorie, Kosmologie Spektrum Akademischer Verlag (1999)
Berry: Kosmologie und Gravitation, Teubner (1990)
Goenner: Einführung in die Kosmologie Spektrum Akad. Verlag (1994)
Silk: Die Geschichte des Kosmos Spektrum Akad. Verlag (1999)
Feitzinger: Kosmische Horizonte Spektrum Akad. Verlag (2002)
Dozent
Period of Event: 12. Apr 2022 - 19. Jul 2022
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Ausbreitungs- und Transportprozesse in Strömungen
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Biomaterialien - biokompatible Materialien (SS 2022)
Vorlesung, donnerstags 09:45-11:15 Uhr, V 9.11; Dozenten: Prof. Dr. G. Tovar, Dr. L. Stegbauer
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Period of Event: 28. Apr 2022 - 21. Jul 2022
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Period of Event: 28. Apr 2022 - 21. Jul 2022
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Biorobotik [Vorlesung]
SoSe 2022, Daniel Häufle
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Carl Schmitts Kritik am Völkerrecht
Status: Offline
Period of Event: 18. Oct 2021 - 18. Feb 2022
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Period of Event: 18. Oct 2021 - 18. Feb 2022
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CFD-Programmier-Seminar
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Colloquium Data Analytics in Engineering
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Computational Methods for Quantitative Finance
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Correspondence Problems in Computer Vision [Vorlesung]
Prof. Dr.-Ing. Andrés Bruhn, Lecture, Summer Term 2022
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Data-Integrated Simulation Science B
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Datenstrukturen und Algorithmen [Übung]
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Datenstrukturen und Algorithmen [Vorlesung]
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Deep Learning - Lecture with Exercise (SS22)
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Period of Event: 1. Apr 2022 - 30. Sep 2022
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Period of Event: 1. Apr 2022 - 30. Sep 2022
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Detection and Pattern Recognition - Exercises
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Detection and Pattern Recognition - Lecture
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Differenzenverfahren hoher Genauigkeit
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Period of Event: 22. Apr 2022 - 31. Jul 2022
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Period of Event: 22. Apr 2022 - 31. Jul 2022
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Dimensionsanalyse
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Dynamics and Control of Legged Locomotion
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Dynamik ereignisdiskreter Systeme
Montag 11:30-13:00 Uhr V 9.31 , Dienstag 9:30 - 11:00 Uhr ISYS Seminarraum , Start am Montag, den 11.04.2022
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Effizient programmieren I
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Einführung in die Biochemie II
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Period of Event: 11. Apr 2022 - 22. Jul 2022
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Period of Event: 11. Apr 2022 - 22. Jul 2022
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Einführung in die Kontinuumsmechanik von Mehrphasenmaterialien [Vorlesung]
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Einführung in die Verbrennung
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Ein- und Mehrphasenströmungen und deren Anwendung in der Industrie
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Elektrische Signalverarbeitung
Montag 09:45 - 11:15 Uhr V47.05; Dienstag 11:30 - 13:00 Uhr V7.11; Start am 11.04.2022
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Emerging Architectures
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Entwicklung Optischer Systeme [Übung]
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Entwicklung Optischer Systeme [Vorlesung]
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Environmental Fluid Mechanics II
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Exercise Machine Learning for Data Science (SS2022)
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Exercise Machine Learning (for Engineering Scientists) [Übung SS22]
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Exercise SM II: Simulation Methods in Practice
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Period of Event: 1. Apr 2022 - 30. Sep 2022
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Period of Event: 1. Apr 2022 - 30. Sep 2022
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Exkursion [Exkursion]
Sommersemester 2022
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Experimentelle Modalanalyse
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Fachpraktikum Methods in Computational EEG
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Finite Elemente Methode im Maschinenbau
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Flexible Mehrkörpersysteme
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Flugzeugaerodynamik I [Übung]
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Flugzeugaerodynamik I [Vorlesung]
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Flugzeugentwurf I
Period of Event: 11. Apr 2022 - 23. Jul 2022
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Funktionalanalysis 2
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Geometric Deep Learning
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Grundlagen der Experimentalphysik II (Thermodynamik und Elektrodynamik) für BSc-Phys, LA Phys, Math, Gewl, TechPäd, SimTech
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Grundlagen der medizinischen Strahlentechnik
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Grundlagen der Optik [Übung]
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Grundlagen der Optik [Vorlesung]
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Gruppenübungen zu Experimentalphysik II für BSc-Phys, Gewl, TechPäd, SimTech
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Halbleiter-Quantenoptik
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Harmonic Analysis
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Period of Event: 11. Apr 2022 - 22. Jul 2022
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Period of Event: 11. Apr 2022 - 22. Jul 2022
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Hauptseminar Einstein Metriken
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Hauptseminar Nichtlineare Differentialgleichungen
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Höhere Analysis / komplexe Analysis für LA
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Höhere Analysis / komplexe Analysis für LA (Gruppenübungen)
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Höhere Analysis / komplexe Analysis für LA (Vortragsübung)
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Höhere Mechanik II: Numerische Methoden der Mechanik
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Imaging Science [Vorlesung]
Prof. Dr.-Ing. Andrés Bruhn, Lecture, Summer Term 2022
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Industrial Aerodynamics
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Period of Event: 12. Apr 2022 - 19. Jul 2022
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Period of Event: 12. Apr 2022 - 19. Jul 2022
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Informationssicherheit und Kryptographie [Hauptseminar]
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Instationäre Gasdynamik und Stoßrohrprobleme
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Intelligent Designs for Machine Learning
Status: Offline
Period of Event: 10. Apr 2022 - 14. Aug 2022
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Period of Event: 10. Apr 2022 - 14. Aug 2022
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Kompressible Strömungen II
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Konstruktion von Discontinuous-Galerkin-Verfahren
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Leichtbau [Vorlesung]
Status: Offline
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Period of Event: 19. Apr 2021 - 7. Apr 2022
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Period of Event: 19. Apr 2021 - 7. Apr 2022
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Lineare Algebra und Analytische Geometrie 2 (Gruppenübungen)
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Luftfahrttechnik
Status: Offline
Period of Event: 14. Apr 2022 - 21. Jul 2022
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Machine Learning [Lecture SS2022]
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Machine Learning [Übung]
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Machine Translation
Lecture (Tue 9:45, 31.01) + practical (Thu 15:45, 55.21), Sebastian Padó. *First lecture material available now. First in-presence meeting Apr 19.*
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Makroökonomik
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Makroökonomik Übung
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Maß- und Wahrscheinlichkeitstheorie
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Maß- und Wahrscheinlichkeitstheorie (Gruppenübungen)
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Masterseminar Blätterungen
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Masterseminar Thin-film flows with non-trivial dynamics
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Mathematische Methoden in der Strömungsmechanik
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Mechanik nichtlinearer Kontinua
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Mehrgrößenregelung [Vorlesung]
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Mehrgrößenregelung [Vorlesung]
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Mensch-Computer-Interaktion [Übung]
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Mensch-Computer-Interaktion [Vorlesung]
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Methode der Finiten Elemente in Statik und Dynamik
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Period of Event: 14. Apr 2022 - 22. Jul 2022
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Period of Event: 14. Apr 2022 - 22. Jul 2022
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Methoden der Unsicherheitsanalyse
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Mikrobiologie f. Ingenieure I
Free places: 37
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Mikroökonomik Modulordner (VL und Ü)
Status: Offline
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Mobile Computing Lab
SS2022
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Modeling of Hydrosystems
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Modelle menschlicher Motorik
SoSe 2022, Daniel Häufle
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Modellierung komplexer Systeme
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Model Predictive Control
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Period of Event: 14. Mar 2022, 00:00 - 22. Jul 2022, 23:55
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Period of Event: 14. Mar 2022, 00:00 - 22. Jul 2022, 23:55
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Molecular Quantum Mechanics
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Molekulare Thermodynamik
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Motion in Human and Machine
SoSe 2022, Daniel Häufle
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Nachhaltige Energie- und Verkehrssysteme
Period of Event: 19. Apr 2022, 14:40 - 1. Oct 2022, 14:45
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Neuropsychologie der Bewegung
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Nichtlineare Optimierung [Übung]
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Period of Event: 25. Apr 2022 - 18. Jul 2022
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Period of Event: 25. Apr 2022 - 18. Jul 2022
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Nichtlineare Optimierung [Vorlesung]
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Nonlinear Control
The entire course is given in English.
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Novel methods in simulation science
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Numerische Grundlagen mit Python
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Numerische Grundlagen [Übung]
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Numerische Grundlagen [Vorlesung]
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Numerische Methoden der Dynamik
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Numerische Modellierung von Mehrphasenströmungen
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Numerische Simulation
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Ökotoxikologie und Bewertung von Schadstoffen
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Optimierungsverfahren für Ingenieuranwendungen
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Physik auf dem Computer
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Plasma Physics 1 (SS 2022)
Was genau ist ein Plasma und wodurch zeichnet es sich aus? In dieser Vorlesung
wird das kollektive Verhalten von Ladungsträgern unter dem Einfluss von elektrischen
und magnetischen Feldern studiert. Beim Übergang zur Flüssigkeitsbeschreibung
des Plasmas helfen Details der Einzelteilchendynamik. Plasmagleichgewichte werden
im Rahmen der Magnetohydrodynamik behandelt, und es wird in die Analyse der
Stabilität solcher Gleichgewichte eingeführt.
Von der Gasentladung über die Ionosphäre bis zum Sonnenplasma: Plasmen als
ungeahnt weit verbreitete Form der Materie bieten breite Anwendungsmöglichkeiten.
Diese Vorlesung bietet die Grundlagen zum Basisverständnis eines Plasmas bzw.
dessen Dynamik.
Period of Event: 11. Apr 2022 - 23. Jul 2022
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Praktikum Echtzeitdatenverarbeitung
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Probabilistik und Monte-Carlo-Methoden
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Program Comprehension
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Programmierparadigmen [Vorlesung]
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Programmierung von Discontinuous-Galerkin-Verfahren
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Proseminar Highlights der Wahrscheinlichkeitstheorie
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Radioaktivität und Strahlenschutz
Nicht obligatorische, jedoch wichtige Basis zum Kurs "Grundlagen der medizinischen Strahlentechnik"
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Period of Event: 14. Apr 2022 - 21. Jul 2022
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Recent Advances in Computer Vision
Prof. Dr.-Ing. Andrés Bruhn, Main Seminar, Summer Term 2022
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Rechnernetze I [Übung]
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Rechnerorganisation 1 [Übung]
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Rechnerorganisation 1 [Vorlesung]
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Reinforcement Learning [Vorlesung]
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Relativitätstheorie 2
Di 11:30-13:00 Uhr in V57.05 (NWZ II)
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Robust Control
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Scientific Visualization [Übung]
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Scientific Visualization [Vorlesung]
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Security and Privacy [Vorlesung]
Prof. Dr. Ralf Küsters/Dr. Daniel Rausch. Lectures on Wednesdays 11:30 & on Thursdays 11:30 (every second week). First lecture on April 13th.
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Selected Topics in the Theories of Plasticity and Viscoelasticity
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Seminar für Mehrphasenströmungen
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Seminar zu Einführung in die Biochemie II (054600000)
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Signal processing and Analysis of human brain potentials (EEG) [Vorlesung]
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Simulation of coupled problems with the Finite Element Method [Vorlesung]
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Spezielle Probleme der Wärmeübertragung
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Stochastische Analysis
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Stochastische Prozesse 1 (Übung)
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Stochastische Prozesse und Modellierung
Eine Schwierigkeit bei der Modellierung eines physikalischen Prozesses ist der Umgang mit Unsicherheiten, beispielsweise verursacht durch fehlende oder mit großen Varianzen behaftete experimentelle Daten oder auch durch mangelndes Wissen über die Mechanismen des Prozesses selbst. Eine Möglichkeit, mit solchen Unsicherheiten umzugehen, ist die stochastische Modellierung und deren Analyse mit stochastischen Methoden.
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Strömungslehre I
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Sustainable development of simulation software
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System and Web Security [Vorlesung]
Prof. Dr. Ralf Küsters. Lectures on Tuesdays 15:45. First lecture on April 12th.
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Systemdynamische Grundlagen der Regelungstechnik (Verfahrenstechnik) [Tutorium]
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Systemdynamische Grundlagen der Regelungstechnik (Verfahrenstechnik) [Vorlesung mit Übung]
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Systementwurf I [Vorlesung]
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Systems Theory in Systems Biology
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Technische Mechanik II
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Technische Mechanik III
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Technische Mechanik III (Tutorium)
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Technische Mechanik III (Übung)
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Technische Mechanik IV
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Technische Strömungslehre
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Technische Thermodynamik II [Vorlesung]
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Theoretische Informatik II [Übung]
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Theoretische Informatik II [Vorlesung]
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Theoretische Physik III: Elektrodynamik
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Theoretische Physik I: Klassische Mechanik
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Theoretische und Computerorientierte Materialtheorie
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Thermodynamik II
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Tutorium Theoretische Physik LA [Tutorium]
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Übung Bayesian Statistics and Probabilistic Machine Learning
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Übungen zu 392340000 Luftfahrtantriebe und Turbomaschinen - freiwillig
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Übungen zu Astrophysik II MSc
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Übungen zu Theo. Physik I, Klassische Mechanik
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Übung zu Halbleiter-Quantenoptik
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Übung zu Relativitätstheorie 2
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Umweltaerodynamik
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Umweltchemie
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Umweltchemie (Praktikum)
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Verhalten und Toxizität von Umweltchemikalien
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Verkehrsflussmodelle
Prof. Dr.-Ing. Markus Friedrich; Vorlesung mit Übung; Montag 14:00-15:30 Uhr; Beginn: 11.04.2022
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Verkehrstechnik und Verkehrsleittechnik
Prof. Dr.-Ing. Markus Friedrich; Vorlesung, Übung & Projektstudie; Dienstag 08:00-11:15 Uhr; Beginn: 12.04.2022
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Virtuelles Engineering
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Vorlesung Bayesian Statistics and Probabilistic Machine Learning
This ILIAS course is dedicated to the lecture "Bayesian Statistics and Probabilistic Machine Learning". If you attend this lecture, please also subscribe to the ILIAS course for the corresponding exercises named "Übung Bayesian Statistics and Probabilisti…
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Vorlesung Datenstrukturen und Algorithmen für SimTech
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Wahrscheinlichkeitstheorie und Statistik II
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Windenergienutzung I - Grundlagen (V)
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