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AG Mathematics of Deep Learning 2020/2021 /CourseID:878
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Audio (MP3)
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
Search course clips:
1
Introduction to Deep Learning
Dr.-Ing. Vincent Christlein
2019-11-14
Free
01:22:04
slides
audio
go to clip page
2
Mathematics - Deep Learning
Prof. Dr. Martin Burger
2019-12-05
Free
01:35:25
slides
slides
audio
go to clip page
3
Known Operator Learning - Towards Integration of Prior Knowledge into Machine Learning
Prof. Dr. Andreas Maier
2020-01-09
Free
00:44:56
slides
slides
audio
go to clip page
4
Biomechanics meets Optimal Control: Predictions of Human Motion
Prof. Dr. Anne Koelewijn
2020-02-13
Free
01:27:21
slides
slides
audio
go to clip page
5
A New Approach for Stochastic Optimization in Deep Learning
Dr. Lukas Pflug
2020-02-20
Free
00:31:51
slides
slides
audio
go to clip page
6
Introduction to Adversarial Robustness for Deep Learning
Leo Schwinn
2020-11-11
Free
00:53:41
slides
go to clip page
7
The interplay of deep learning and control theory
2020-12-09
Free
01:04:25
slides
go to clip page
8
Generalised Perceptron Learning
2020-12-16
Free
01:10:53
slides
go to clip page
9
Neuromorphic Computing and its Mathematical Challenges
2021-01-13
Free
01:17:23
slides
go to clip page
More courses from Dr. Daniel Tenbrinck
AG Mathematics of Deep Learning 2020/2021
Dr. Daniel Tenbrinck
lecture
2021-01-13
Free
Mathematical Data Science 1 2020
Dr. Daniel Tenbrinck
lecture
2020-07-22
Free / IdM-login
Discrete Graph Operators for Manifold-Valued Data
Dr. Daniel Tenbrinck
2020-11-04
IdM-login
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