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Instructors: Dr. rer. pol. Steffen Eger
Event type:
Seminar
Org-unit: Dept. 20 - Computer Science
Displayed in timetable as:
20-00-1086
Subject:
Crediting for:
Hours per week:
2
Language of instruction:
Englisch
Min. | Max. participants:
- | -
Course Contents:
Based on the current revolution in deep learning and artificial intelligence, one of the questions we ask in the seminar is whether such revolutions can be predicted in advance. Further issues discussed:
- Problems and aspects of peer-reviewing
- citation count prediction
- poor research practices: biases in research, poor study design, abuse of statistics, false claim of superiority of one method over another
- citation cartels & cliques
- ethics in research, including self-citations, and forms of cheating
The seminar will be held as a block seminar and in English (about 2-3 half day sessions).
Further organisational details can be found here: https://github.com/SteffenEger/MetaScience
Preconditions:
Mathematical and/or statistical background/affinity is helpful.
Deep Learning (for NLP) may also be helpful.
Additional Information:
The seminar will be held as a block seminar and in English (about 2-3 half day sessions).
Further organisational details can be found here: https://github.com/SteffenEger/MetaScience
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