AG Mathematics of Deep Learning /KursID:878
- Letzter Beitrag vom 2021-07-26
Schlüsselworte: functional minimization methods framework approximation control distance reconstruction energy deep search basic weights models measure layer activation problem example propagation

Lehrende(r)

Dr. Daniel Tenbrinck

Einrichtung

Lehrstuhl für Angewandte Mathematik

Aufzeichnungsart

Vortragsreihe

Sprache

Zugehörige Einzelbeiträge

Folge
Titel
Lehrende(r)
Aktualisiert
Zugang
Dauer
Medien
1
Introduction to Deep Learning
Dr.-Ing. Vincent Christlein
2019-11-14
Frei
01:22:04
2
Mathematics - Deep Learning
Prof. Dr. Martin Burger
2019-12-05
Frei
01:35:25
3
Known Operator Learning - Towards Integration of Prior Knowledge into Machine Learning
Prof. Dr. Andreas Maier
2020-01-09
Frei
00:44:56
4
Biomechanics meets Optimal Control: Predictions of Human Motion
Prof. Dr. Anne Koelewijn
2020-02-13
Frei
01:27:21
5
A New Approach for Stochastic Optimization in Deep Learning
Dr. Lukas Pflug
2020-02-20
Frei
00:31:51
6
Introduction to Adversarial Robustness for Deep Learning
Leo Schwinn
2020-11-11
Frei
00:53:41
7
The interplay of deep learning and control theory
2020-12-09
Frei
01:04:25
8
Generalised Perceptron Learning
2020-12-16
Frei
01:10:53
9
Neuromorphic Computing and its Mathematical Challenges
2021-01-13
Frei
01:17:23
10
Structure Preserving Deep Learning
2021-01-27
Frei
01:07:37
11
Mathematical aspects of neural network approximation and learning
2021-04-20
Frei
01:02:09
12
Deep Learning meets Shearlets: On the Path Towards Interpretable Imaging
2021-04-27
Frei
00:50:44
13
On the Confluence of Deep Learning and Energy Minimization Methods for Inverse Problems
2021-05-04
IdM-Anmeldung
00:53:30
14
Neural Differential Equations, Control and Machine Learning
2021-05-11
Frei
00:57:53
15
An Introduction to Generative Modeling
2021-05-18
Frei
00:55:59
16
Random walks and PDEs in graph-based learning
2021-05-25
Frei
01:00:32
17
Learning with energy-based models
2021-06-01
Frei
01:04:59
18
Learning of Wasserstein Generative Models and Patch-based Texture Synthesis
2021-06-08
Frei
01:01:40
19
Self-supervised Learning for 3D Shape Analysis
2021-06-18
Frei
00:34:20
20
Deep Learning for Computed Tomography Image Reconstruction from Insufficient Data
Dr. Yixing Huang
2021-06-26
Frei
00:41:12
21
Deeply learned regularisation for inverse problems
2021-06-29
Frei
00:58:36
22
Online Learning for Optimization Problems with Unknown or Uncertain Cost Functions
2021-07-06
Frei
00:29:47
23
Biomechanics meets Deep Learning
Prof. Dr. Anne Koelewijn
2021-07-13
Frei
01:10:13
24
Accelerated Forward-Backward Optimization using Deep Learning
2021-07-26
Frei
00:46:52

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