Publications

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2017
Haußmann, M, Hamprecht, F A and Kandemir, M (2017). Variational Bayesian Multiple Instance Learning with Gaussian Processes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 6570-6579PDF icon Technical Report (1.29 MB)
2016
von Borstel, M, Kandemir, M, Schmidt, P, Rao, M, Rajamani, K and Hamprecht, F A (2016). Gaussian process density counting from weak supervision. ECCV. Proceedings. Springer. LNCS 9905 365-380 PDF icon Technical Report (1.71 MB)
Kandemir, M, Haußmann, M, Diego, F, Rajamani, K, van der Laak, J and Hamprecht, F A (2016). Variational weakly-supervised Gaussian processes. BMVC. ProceedingsPDF icon Technical Report (3.28 MB)
2015
Kandemir, M and Hamprecht, F A (2015). The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors. NIPS. Proceedings. 44 145-159PDF icon Supplementary Material (223.39 KB)PDF icon Technical Report (2.58 MB)
2014
Kandemir, M, Rubio, J C, Schmidt, U, Wojek, C, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. Medical Image Computing and Computer-Assisted Intervention. Springer. 154--161PDF icon Technical Report (2 MB)