| Schools |
30.06. -
05.07.2019 | Ninth
European Big Data Management & Analytics Summer School (eBISS 2019) in Berlin,
Germany, lecture "Spectral graph theory for data visualization and feature
extraction" |
10. - 12.03.2009 | Interdisciplinary College IK2009 in Günne,
Germany, special course SC3 "Slow Feature Analysis: Theory and
Applications" |
13. - 17.08.2007 | FIAS
Summer School in Frankfurt, Germany, lecture "Slowness, sparseness, statistical
independence: principles of unsupervised learning in visual processing" |
05. - 07.03.2004 | Interdisciplinary College IK2004 in Günne,
Germany, basic course BC2 "Neural Computation"
|
|
|
| RUB-INI |
SS 2025 |
Mathematics for Modeling and Data Analysis (211047/211247) |
SS 2025 |
Introduction to Artificial Intelligence (211045) (partly) |
SS 2025 |
Computational Neuroscience: Vision and Memory (211049/211249) |
WS 2024/2025 |
Machine Learning: Unsupervised Methods (with Problem Based Learning) (212501) |
SS 2024 |
Mathematics for Modeling and Data Analysis (211047/211247) |
SS 2024 |
Introduction to Artificial Intelligence (211045) (partly) |
09.02. - 22.02.2024 |
Theoretical Neuroscience (IGSN graduate program) |
SS 2023 |
Introduction to Artificial Intelligence (211045) (partly) |
27.01. - 17.02.2023 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2022/2023 |
Machine Learning: Unsupervised Methods (with Problem Based Learning) (212501) |
SS 2022 |
Mathematics for Modeling and Data Analysis (211047/211247) |
SS 2022 |
Introduction to Artificial Intelligence (211045) (partly) |
SS 2022 |
Computational Neuroscience: Vision and Memory (211049/211249) |
SS 2022 - SS 2024 |
Reduced teaching load as a Dean of the faculty. |
04.02. - 18.02.2022 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2021/2022 |
Machine Learning: Unsupervised Methods (with Problem Based Learning) (310003/310013) |
SS 2021 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2021 |
Computational Neuroscience: Vision and Memory (310504/310514) |
SS 2021 |
Introduction to Artificial Intelligence (310502/310512) (partly) |
28.01. - 11.02.2021 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2020/2021 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2020 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2020 |
Computational Neuroscience: Vision and Memory (310504/310514) |
14.02. - 13.03.2020 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2019/2020 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2019 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2019 |
Computational Neuroscience: Vision and Memory (310504/310514) |
SS 2019 |
Master Seminar: Machine Learning for Student Projects in Engineering (310028) |
SS 2019 |
Basics and Applications of Machine / Deep Learning in Engineering and Natural Sciences - an Overview (160003) |
01.02. - 22.02.2019 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2018/2019 |
Machine Learning: Unsupervised Methods (310003/310013) |
WS 2018/2019 |
Master Seminar: Machine Learning for Student Projects in Engineering (310028) |
SS 2018 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2018 |
Computational Neuroscience: Vision and Memory (310504/310514) |
20.10.2017 - 09.02.2018 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2017/2018 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2017 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2017 |
Computational Neuroscience: Vision and Memory (310504/310514) |
03.02. - 03.03.2017 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2016/2017 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2016 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2016 |
Computational Neuroscience: Vision and Memory (310504/310514) |
29.01. - 26.02.2016 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2015/2016 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2015 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2015 |
Computational Neuroscience: Vision and Memory (310504/310514) |
30.01. - 27.02.2015 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2014/2015 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2014 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2014 |
Computational Neuroscience: Vision and Memory (310504/310514) |
31.01. - 28.02.2014 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2013/2014 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2013 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2013 |
Computational Neuroscience: Vision and Memory (310504/310514) |
01.02. - 01.03.2013 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2012/2013 |
Machine Learning: Unsupervised Methods (310003/310013) |
SS 2012 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2012 |
Computational Neuroscience: Vision and Memory (310504/310514) |
20.01. - 17.02.2012 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2011/2012 |
Machine Learning: Basic Course (310003/310013) |
SS 2011 |
Mathematics for Modeling and Data Analysis (310503/310513) |
SS 2011 |
Computational Neuroscience: Vision and Memory (310504/310514) |
21.01. - 18.02.2011 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2010/2011 |
Machine Learning: Basic Course (310003) |
WS 2010/2011 |
Seminar: Model-based Data Analysis (310023) |
SS 2010 |
Mathematics for Modeling and Data Analysis (310003) |
SS 2010 |
Computational Neuroscience: Vision and Memory (310203) |
SS 2010 |
Seminar: Model-based Data Analysis (310023) |
22.01. - 19.02.2010 |
Theoretical Neuroscience (IGSN graduate program) |
WS 2009/2010 |
Machine Learning: Basic Course |
WS 2009/2010 |
Seminar: Model-based Data Analysis |
SS 2009 |
Mathematische Methoden der Neuroinformatik (310003) |
SS 2009 |
Computational Neuroscience: Vision and Memory (310203) |
SS 2009 |
Seminar: Model-based Data Analysis |
|
|
| HU-ITB |
SS 2009 |
Models of Higher Brain Functions |
WS 2008/2009 |
Models of Neural Systems (3110451) |
29.09. - 02.10.2008 |
Computational Neuroscience (Mind & Brain graduate program) |
29.09. - 10.10.2008 |
Mathematics for Theoretical Biologists |
SS 2008 |
Mathematik für Biolog(inn)en III (31179) |
SS 2008 |
Models of Higher Brain Functions (31111) |
SS 2008 |
Computational Neuroscience - Oberseminar (31173) |
WS 2007/2008 |
Neural Networks and Machine Learning |
WS 2007/2008 |
Models of Neural Systems (31064 [BXY-27], 31143) |
WS 2007/2008 |
23 Problems in Systems Neuroscience - Oberseminar |
WS 2007/2008 |
Computational Neuroscience - Oberseminar |
SS 2007 |
Mathematik für Biolog(inn)en III (31032) |
SS 2007 |
Models of Higher Brain Functions (31200) |
SS 2007 |
Computational Neuroscience - Oberseminar (31192) |
WS 2006/2007 |
Datenanalyse und stochastische Prozesse (31164) |
WS 2006/2007 |
Models of Neural Systems |
WS 2006/2007 |
Computational Neuroscience - Oberseminar |
SS 2006 |
Mathematik für Biolog(inn)en III (31031)
|
SS 2006 |
Neuronale Netze und Maschinelles Lernen (31192) |
SS 2006 |
Computational Neuroscience - Oberseminar (31196) |
WS 2005/2006 |
Datenanalyse und stochastische Prozesse (31162) |
WS 2005/2006 |
Computational Neuroscience III: Theory of Neuronal Systems (31161) |
WS 2005/2006 |
Computational Neuroscience - Oberseminar (31170) |
SS 2005 |
Mathematik für Biolog(inn)en III (31030) |
SS 2005 |
Computational Neuroscience - Oberseminar (31197) |
WS 2004/2005 |
Datenanalyse und stochastische Prozesse |
WS 2004/2005 |
Computational Neuroscience - Oberseminar (31178) |
SS 2004 |
Mathematik für Biolog(inn)en III (31028) |
SS 2004 |
Computational Neuroscience - Oberseminar (31187) |
WS 2003/2004 |
Datenanalyse und stochastische Prozesse |
WS 2003/2004 |
Computational Neuroscience III: Theory of Neural Networks |
SS 2003 |
Computational Neuroscience V: Seminar on ''Learning and Memory'' |
SS 2003 |
Mathematik für Biologen III |
WS 2002/2003 |
Künstliche neuronale Netze |
SS 2002 |
Mathematik für Biologen III |
WS 2001/2002 |
Theorie neuronaler Netzwerke |
SS 2001 |
Neuronale Codierung: Datenanalyse und Informationstheorie |
WS 2000/2001 |
Mathematik für Biologen I - Übungen |
SS 2000 |
Spielen lernen |
WS 1999/2000 |
Theorie neuronaler Systeme |