AG Mathematics of Deep Learning 2020/2021 /CourseID:878

Detailed information

Keywords: functional minimization methods framework approximation control distance reconstruction energy deep search basic weights models measure layer activation problem example propagation

Most recent entry on 2021-01-13 

Lecturer

Dr. Daniel Tenbrinck

Organisational Unit

Lehrstuhl für Angewandte Mathematik

Recording type

Vorlesungsreihe

Via

Free

Language

German

Associated Clips

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction to Deep Learning preview image
Introduction to Deep Learning
Dr.-Ing. Vincent Christlein
2019-11-14
Free
01:22:04
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2
Mathematics - Deep Learning preview image
Mathematics - Deep Learning
Prof. Dr. Martin Burger
2019-12-05
Free
01:35:25
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3
Known Operator Learning - Towards Integration of Prior Knowledge into Machine Learning preview image
Known Operator Learning - Towards Integration of Prior Knowledge into Machine Learning
Prof. Dr. Andreas Maier
2020-01-09
Free
00:44:56
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4
Biomechanics meets Optimal Control: Predictions of Human Motion preview image
Biomechanics meets Optimal Control: Predictions of Human Motion
Prof. Dr. Anne Koelewijn
2020-02-13
Free
01:27:21
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5
A New Approach for Stochastic Optimization in Deep Learning preview image
A New Approach for Stochastic Optimization in Deep Learning
Dr. Lukas Pflug
2020-02-20
Free
00:31:51
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6
Introduction to Adversarial Robustness for Deep Learning preview image
Introduction to Adversarial Robustness for Deep Learning
Leo Schwinn
2020-11-11
Free
00:53:41
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7
The interplay of deep learning and control theory preview image
The interplay of deep learning and control theory
2020-12-09
Free
01:04:25
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8
Generalised Perceptron Learning preview image
Generalised Perceptron Learning
2020-12-16
Free
01:10:53
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9
Neuromorphic Computing and its Mathematical Challenges preview image
Neuromorphic Computing and its Mathematical Challenges
2021-01-13
Free
01:17:23
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