Jakob Ambsdorf

15 papers B 1Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning. CoRR Asbjørn Munk, Stefano Cerri, Jakob Ambsdorf, Julia Machnio, Sebastian Nørgaard Llambias, Vardan Nersesjan, Christian Hedeager Krag, Peirong Liu, Pablo Rocamora-García, Mostafa Mehdipour-Ghazi, Mikael Boesen, Michael Eriksen Benros, Juan Eugenio Iglesias, Mads Nielsen
2025	J	`jnl`	DIET-CP: Lightweight and Data Efficient Self Supervised Continued Pretraining. CoRR Bryan Rodas, Natalie Montesino, Jakob Ambsdorf, David A. Klindt, Randall Balestriero
2025	—	`conf`	General Methods Make Great Domain-Specific Foundation Models: A Case-Study on Fetal Ultrasound. MICCAI (7) Jakob Ambsdorf, Asbjørn Munk, Sebastian Nørgaard Llambias, Anders Nymark Christensen, Kamil Wojciech Mikolaj, Randall Balestriero, Martin Grønnebæk Tolsgaard, Aasa Feragen, Mads Nielsen
2025	J	`jnl`	General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound. CoRR Jakob Ambsdorf, Asbjørn Munk, Sebastian Nørgaard Llambias, Anders Nymark Christensen, Kamil Wojciech Mikolaj, Randall Balestriero, Martin Grønnebæk Tolsgaard, Aasa Feragen, Mads Nielsen
2024	J	`jnl`	AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation. CoRR Asbjørn Munk, Jakob Ambsdorf, Sebastian Nørgaard Llambias, Mads Nielsen
2024	—	`conf`	Learning Semantic Image Quality for Fetal Ultrasound from Noisy Ranking Annotation. ISBI Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer, Zahra Bashir, Chun Kit Wong, Paraskevas Pegios, Alberto Raheli, Morten Bo Søndergaard Svendsen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen
2024	J	`jnl`	Learning semantic image quality for fetal ultrasound from noisy ranking annotation. CoRR Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer, Zahra Bashir, Chun Kit Wong, Paraskevas Pegios, Alberto Raheli, Morten Bo Søndergaard Svendsen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen
2024	—	`conf`	Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models. ASMUS@MICCAI Markus Ditlev Sjøgren Olsen, Jakob Ambsdorf, Manxi Lin, Caroline Taksøe-Vester, Morten Bo Søndergaard Svendsen, Anders Nymark Christensen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Aasa Feragen, Paraskevas Pegios
2024	J	`jnl`	Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models. CoRR Markus Ditlev Sjøgren Olsen, Jakob Ambsdorf, Manxi Lin, Caroline Taksøe-Vester, Morten Bo Søndergaard Svendsen, Anders Nymark Christensen, Mads Nielsen, Martin Grønnebæk Tolsgaard, Aasa Feragen, Paraskevas Pegios
2024	J	`jnl`	Yucca: A Deep Learning Framework For Medical Image Analysis. CoRR Sebastian Nørgaard Llambias, Julia Machnio, Asbjørn Munk, Jakob Ambsdorf, Mads Nielsen, Mostafa Mehdipour-Ghazi
2023	J	`jnl`	Benchmarking Faithfulness: Towards Accurate Natural Language Explanations in Vision-Language Tasks. CoRR Jakob Ambsdorf
2022	B	`conf`	Explain yourself! Effects of Explanations in Human-Robot Interaction. RO-MAN Jakob Ambsdorf, Alina Munir, Yiyao Wei, Klaas Degkwitz, Harm Matthias Harms, Susanne Stannek, Kyra Ahrens, Dennis Becker, Erik Strahl, Tom Weber, Stefan Wermter
2022	J	`jnl`	Explain yourself! Effects of Explanations in Human-Robot Interaction. CoRR Jakob Ambsdorf, Alina Munir, Yiyao Wei, Klaas Degkwitz, Harm Matthias Harms, Susanne Stannek, Kyra Ahrens, Dennis Becker, Erik Strahl, Tom Weber, Stefan Wermter
2022	J	`jnl`	Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations. CoRR Björn Plüster, Jakob Ambsdorf, Lukas Braach, Jae Hee Lee, Stefan Wermter
2022	J	`jnl`	What's on Your Mind, NICO? Künstliche Intell. Matthias Kerzel, Jakob Ambsdorf, Dennis Becker, Wenhao Lu, Erik Strahl, Josua Spisak, Connor Gaede, Tom Weber, Stefan Wermter