| 2019 | MICCAI | How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning. | Maximilian Blendowski, Hannes Nickisch, Mattias P. Heinrich |
| 2018 | ICML | State Space Gaussian Processes with Non-Gaussian Likelihood. | Hannes Nickisch, Arno Solin, Alexander Grigorevskiy |
| 2017 | MICCAI | Learning a Sparse Database for Patch-Based Medical Image Segmentation. | Moti Freiman, Hannes Nickisch, Holger Schmitt, Pl Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen |
| 2016 | AISTATS | Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. | William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing |
| 2015 | ICML | Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. | Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola |
| 2015 | ICML | Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP). | Andrew Gordon Wilson, Hannes Nickisch |
| 2015 | MICCAI | Learning Patient-Specific Lumped Models for Interactive Coronary Blood Flow Simulations. | Hannes Nickisch, Yechiel Lamash, Sven Prevrhal, Moti Freiman, Mani Vembar, Liran Goshen, Holger Schmitt |
| 2012 | MICCAI | From Image to Personalized Cardiac Simulation: Encoding Anatomical Structures into a Model-Based Segmentation Framework. | Hannes Nickisch, Hans Barschdorf, Frank M. Weber, Martin W. Krueger, Olaf Dssel, Jrgen Weese |
| 2009 | CVPR | Learning to detect unseen object classes by between-class attribute transfer. | Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling |
| 2009 | ICML | Convex variational Bayesian inference for large scale generalized linear models. | Hannes Nickisch, Matthias W. Seeger |
| 2008 | ICML | Compressed sensing and Bayesian experimental design. | Matthias W. Seeger, Hannes Nickisch |