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Jann Goschenhofer
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Books and Theses
- 2023
- [b1]Jann Goschenhofer:
Reducing the effort for data annotation: contributions to weakly supervised deep learning. Ludwig Maximilian University of Munich, Germany, 2023
Journal Articles
- 2023
- [j1]Sai Rahul Kaminwar
, Jann Goschenhofer, Janek Thomas, Ingo Thon, Bernd Bischl:
Structured Verification of Machine Learning Models in Industrial Settings. Big Data 11(3): 181-198 (2023)
Conference and Workshop Papers
- 2023
- [c5]Matthias Aßenmacher, Lukas Rauch, Jann Goschenhofer, Andreas Stephan, Bernd Bischl, Benjamin Roth, Bernhard Sick:
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering. IAL@PKDD/ECML 2023: 65-73 - [c4]Jann Goschenhofer, Bernd Bischl, Zsolt Kira:
ConstraintMatch for Semi-constrained Clustering. IJCNN 2023: 1-10 - [c3]Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin:
Approximately Bayes-optimal pseudo-label selection. UAI 2023: 1762-1773 - 2021
- [c2]Jann Goschenhofer, Rasmus Hvingelby
, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl:
Deep Semi-supervised Learning for Time Series Classification. ICMLA 2021: 422-428 - 2019
- [c1]Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas:
Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning. ECML/PKDD (3) 2019: 400-415
Informal and Other Publications
- 2023
- [i7]Cem Akkus, Luyang Chu, Vladana Djakovic, Steffen Jauch-Walser, Philipp Koch, Giacomo Loss, Christopher Marquardt, Marco Moldovan, Nadja Sauter, Maximilian Schneider, Rickmer Schulte, Karol Urbanczyk, Jann Goschenhofer, Christian Heumann, Rasmus Hvingelby, Daniel Schalk, Matthias Aßenmacher:
Multimodal Deep Learning. CoRR abs/2301.04856 (2023) - [i6]Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin:
Approximate Bayes Optimal Pseudo-Label Selection. CoRR abs/2302.08883 (2023) - [i5]Jann Goschenhofer, Bernd Bischl, Zsolt Kira:
ConstraintMatch for Semi-constrained Clustering. CoRR abs/2311.15395 (2023) - 2022
- [i4]Emilio Dorigatti, Jann Goschenhofer, Benjamin Schubert, Mina Rezaei, Bernd Bischl:
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection. CoRR abs/2201.13192 (2022) - 2021
- [i3]Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl:
Deep Semi-Supervised Learning for Time Series Classification. CoRR abs/2102.03622 (2021) - 2019
- [i2]Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas:
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning. CoRR abs/1904.10829 (2019) - [i1]Kamer Ali Yuksel, Jann Goschenhofer, Hridya V. Varma, Urban Fietzek, Franz Michael Josef Pfister:
Granular Motor State Monitoring of Free Living Parkinson's Disease Patients via Deep Learning. CoRR abs/1911.06913 (2019)
Coauthor Index
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