Colloquium

Schedule

Date Topic Lead
11.03.2020 “How Good Is Your Evidence and How Would You Know?” by Hahn et al
 Christian
18.03.2020 Paper review
25.03.2020 “Pattern Recognition and Machine Learning” by Bishop, Section 4.2
01.04.2020 “Pattern Recognition and Machine Learning” by Bishop, Section 9.2
08.04.2020 “Pattern Recognition and Machine Learning” by Bishop, Section 9.3 Anatol, Tobias
15.04.2020 “Pattern Recognition and Machine Learning” by Bishop, Section 9.4 Franziska, Benedikt
22.04.2020 “Academic Writing for Graduate Students” by Swales and Feak, pages 284-305 Benjamin, Patrick, Franziska
29.04.2020 Research discussion Tobias
06.05.2020 “Academic Writing for Graduate Students” by Swales and Feak, pages 305-326 Benedikt, Anatol, Christian, Tobias
03.06.2020 “Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning” by Quiring et al. Anatol, Benedikt
10.06.2020 “A Metric Learning Reality Check” by Musgrave et al. Tobias
17.06.2020
  • Robust Image Forensics From Rounding Artifacts
  • Reliable Camera Model Identification
  • Benjamin Schiller
  • Jiarong Pan
24.06.2020 No colloquium
01.07.2020 TBD Patrick
08.07.2020 TBD Franziska
15.07.2020 TBD Benjamin
22.07.2020 TBD Anatol oder Benedikt

Archive

 

 

Date Topic Lead
15.05.2019 Triplet loss for deep metric learning Amir
22.05.2019 Research collaboration experiences Christian
29.05.2019 “Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking” by Quiring et al. Benedikt
05.06.2019 Incremental Learning Techniques for Face Recognition Tobias
12.06.2019
  • Deep Metric Learning for Content-Based Image Retrieval on Unlabelled Data
  • Robustness of GOP Identification in Strongly Double Compressed H.264 Videos
  • Zhou Gui
  • Dominik Wassermann
19.06.2019 Camera model identification Patrick
24.06.2019 Forensic investigation of generative residual noise models Qian Zhang
26.06.2019 Image forensics from chroma wrinkles Benedikt
03.07.2019 Room 02.152-113
  • Deciphering severely degraded European license plates
  • “Weight Uncertainty in Neural Networks” by Blundell et al. – pt.1
  • Paula Kaiser
  • Anatol Maier
10.07.2019 No colloquium
17.07.2019 Exposing spliced images by inconsistencies in learned color statistics Lei Su
24.07.2019 “Weight Uncertainty in Neural Networks” by Blundell et al. – pt.2 Anatol Maier
31.07.2019 Internal meeting
07.08.2019 Image Restoration for Image Classification Kang Wang
21.08.2019 Drafting Guidelines for “Writing a scientific thesis” – pt.1 MMSec Group
28.08.2019 Drafting Guidelines for “Writing a scientific thesis” – pt.2 MMSec Group
04.09.2019 Drafting Guidelines for “Writing a scientific thesis” – pt.3 MMSec Group
11.09.2019 Retreat of entire Lab to Waischenfeld
18.09.2019 Robustness of GOP Identification in Strongly Double Compressed H.264 Videos Dominik Wassermann
06.11.2019 Internal meeting
13.11.2019 Internal meeting
20.11.2019 Introduction to TensorFlow Benedikt, Anatol
27.11.2019 Practical working skills:
  • Fundamentals of python’s pandas library
  • Remote debugging in PyCharm
 MMSec Group:
  • Patrick
  • Franziska
04.12.2019 Learning to Decipher License Plates in Severely Degraded Images Paula Kaiser
11.12.2019 “Why Should I Trust You?”: Explaining the Predictions of Any Classifier by Ribeiro et al. Katja
18.12.2019 Democracies and disinformation Christian
08.01.2020 Internal meeting
15.01.2020 Internal meeting
22.02.2020 No colloquium
29.01.2020 “Exploring Randomly Wired Neural Networks for Image Recognition” by Xie et al. Franziska
05.02.2020 No colloquium
12.02.2020 Internal meeting
18.02.2020 First batch of blog posts
26.02.2020 No colloquium