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Instructors: Prof. Dr. Nassir Navab, Anees Kazi, Roger Soberanis, Mahsa Ghorbani
Inhalt
Announcements
- 13.12.2021 - The recorded video of the first lecture has been added to the schedule.
- 22.10.2021 - The schedule have has been released.
- 13.10.2021 - Let us know your four preferred papers by email by Sun. 17.10
- 13.10.2021 - List of topics has been published.
- 12.10.2021 - The list of papers will be published on October 13th. Further details will be sent to the participants via email.
- 12.10.2021 - The classes will start on November 2nd, 12:00 pm - 2 pm CET.
- 15.07.2021 - Registrations are open from 15.07.2021 to 20.07.2021 through the TUM Matching Platform. Additionally, let us know your interest through our application form.
- 12.07.2021 - The slides of the preliminary meeting are available here (slides).
- 05.07.2021 - Course Wiki is up!
- 05.07.2021 - Contact information. If you have any questions about the seminar, feel free to contact Roger Soberanis (roger.soberanis@tum.de) or Anees Kazi (anees.kazi@tum.de)
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| Date | Time | Place | Topic | Tutor (email) | Student | Additional Info/ slides |
|---|---|---|---|---|---|---|
| 2.11.21 | 12:00 - 14:00 | Intro to GDLMA I | Video Lecture | |||
| 9.11.21 | 12:00 - 14:00 | Intro to GDLMA II | ||||
16.11.21 | 12:00 - 14:00 | GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs | Farid (mf.azampour@gmail.com) | Nicolas Peter | ||
| Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image. | Mahdi (m.saleh@tum.de) | Stella Dimitra | ||||
| Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose | Lennart (lennart.bastian@tum.de) | Dominik | ||||
23.11.21 | 12:00 - 14:00 | |||||
| Project presentation by CAMP: Graph Deep Learning for Healthcare Applications. | Dr. Anees Kazi | |||||
30.11.21 | 12:00 - 14:00 | INTERPRETING GRAPH NEURAL NETWORKS FOR NLP WITH DIFFERENTIABLE EDGE MASKING | Yousef (ashkan.khakzar@tum.de ) | Jingpei | ||
| Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method | Ashkan (ashkan.khakzar@tum.de ) | Armin | ||||
| Disentangled Graph Convolutional Networks | Azade (azade.farshad@tum.de ) | Ahmed Alaaeldin Fathy Hanafy | ||||
7.12.21 | 12:00 - 14:00 | |||||
| Project presentation by CAMP | Dr. Hendrik Burwinkel | |||||
14.12.21 | 12:00 - 14:00 | Multi-label zero-shot learning with graph convolutional networks | Alaa / Anees (anees.kazi@tum.de) | Mohamed Taieb | ||
| Learning Graph Convolutional Networks for Multi-Label Recognition and Applications | Mahsa (mahsa.ghorbani@tum.de) | Simay | ||||
| BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis | Shahrooz (hahrooz.faghihroohi@tum.de) | Amine | ||||
21.12.21 | 12:00 - 14:00 | |||||
| Project presentation by CAMP | ||||||
28.12.21 | 12:00 - 14:00 | |||||
| No Session | ||||||
4.01.22 | 12:00 - 14:00 | |||||
| No Session | ||||||
11.01.22 | 12:00 - 14:00 | Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis | Mathias (matthias.keicher@tum.de) | Sergei | ||
| A mutual multi-scale triplet graph convolutional network for classification of brain disorders using functional or structural connectivity | Shahrooz (hahrooz.faghihroohi|[at]|tum.de) | Nicolas Robert Baptiste | ||||
| Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks | Anees (anees.kazi@tum.de) | Erekle | ||||
18.01.22 | 12:00 - 14:00 | |||||
| Project presentation by CAMP | ||||||
25.01.22 | 12:00 - 14:00 | SGNET: Structure-Aware Graph-Based Networks for Airway Semantic Segmentation | Roger (roger.soberanis@tum.de) | Janik | ||
| Hybrid graph convolutional neural networks for landmark-based anatomical segmentation | Tariq (t.bdair@tum.de) | Farid | ||||
| Early Detection of Liver Fibrosis Using Graph Convolutional Networks | Mahsa (mahsa.ghorbani@tum.de) | Sener | ||||
1.02.21 | 12:00 - 14:00 | |||||
| Project presentation by CAMP | ||||||
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