Thesis category: MA thesis

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18JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Unsupervised Learning – Part 1 (WS 20/21)
In this video, we introduce the topic of unsupervised learning and start looking at Restricted Boltzmann Machines as one of the first approaches for Unsupervised Deep Learning. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Unsupervised Learning – Part 1 (WS 20/21)
17JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 28 – Laplacian Support Vector Machines
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 28 – Laplacian Support Vector Machines
17JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 27 – Kernel PCA and Sequence Kernels
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 27 – Kernel PCA and Sequence Kernels
16JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 26 – Mercer’s Theorem and the Kernel SVM
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 26 – Mercer’s Theorem and the Kernel SVM
16JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 25 – Support Vector Machines – Optimization
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 25 – Support Vector Machines – Optimization
15JAN 2021
News
Invited Talk by Matthias Niessner – Jan 21st 2021, 12h CET
It is a great pleasure to announce a new guest presentation by Matthias Niessner from TU Munich! Title: 3D Semantic Scene UnderstandingDate: 21st of January, 2021, 12h, noon CETLocation: https://fau.zoom.us/j/93218875951?pwd=TXdVdi9nVTVRa09ya1V2aWk5Z0d1UT09 Abstract: In recent years, commodity 3D sensors, such as the Microsoft Kinect, have become easily and widely available. These advances in sensing technology have inspired significant […]It is a great pleasure to announce a new guest presentation by Matthias Niessner from TU Munich! Title: 3D Semantic Scene UnderstandingDate: 21st of January, 2021, 12h, noon CETLocation: https://fau.zoom.us/j/93218875951?pwd=TXdVdi9nVTVRa09ya1V2aWk5Z0d1UT09 Abstract: In recent years, commodity 3D sensors, such as the Microsoft Kinect, have become easily and widely available. These advances in sensing technology have inspired significant […]
Read more about Invited Talk by Matthias Niessner – Jan 21st 2021, 12h CET