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121.
Senapati, J.* et al.: Bayesian neural networks for uncertainty estimation of imaging biomarkers. Lect. Notes Comput. Sc. 12436 LNCS, 270-280 (2020)
122.
Behzadi, S.* ; Müller, N.S. ; Plant, C.* & Böhm, C.*: Clustering of mixed-type data considering concept hierarchies. Lect. Notes Comput. Sc. 11439 LNAI, 555-573 (2019)
123.
Ghosh, D.* ; Tetko, I.V. ; Klebl, B.* ; Nussbaumer, P.* & Koch, U.*: Analysis and modelling of false positives in GPCR assays. Lect. Notes Comput. Sc. 11731 LNCS, 764-770 (2019)
124.
Karpov, P. ; Godin, G.* & Tetko, I.V.: A transformer model for retrosynthesis. Lect. Notes Comput. Sc. 11731 LNCS, 817-830 (2019)
125.
Mishra, M. et al.: Quantifying structural heterogeneity of healthy and cancerous mitochondria using a combined segmentation and classification USK-net. Lect. Notes Comput. Sc. 11731 LNCS, 289-298 (2019)
126.
Peng, T. ; Boxberg, M.* ; Weichert, W.* ; Navab, N.* & Marr, C.: Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval. Lect. Notes Comput. Sc. 11764 LNCS, 676-684 (2019)
127.
Sadafi, A. et al.: Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy. Lect. Notes Comput. Sc. 11764 LNCS, 685-693 (2019)
128.
Schneider, M. ; Wang, L. & Marr, C.: Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets. Lect. Notes Comput. Sc. 11728 LNCS, 673-686 (2019)
129.
Schulte-Sasse, R.* ; Budach, S.* ; Hnisz, D.* & Marsico, A.: Graph convolutional networks improve the prediction of cancer driver genes. Lect. Notes Comput. Sc. 11731 LNCS, 658-668 (2019)
130.
Tetko, I.V. ; Theis, F.J.* ; Karpov, P. & Kůrková, V.: Preface. Lect. Notes Comput. Sc. 11727 LNCS, v-vii (2019)
131.
Tetko, I.V. ; Theis, F.J. ; Karpov, P. & Kůrková, V.*: Preface. Lect. Notes Comput. Sc. 11728 LNCS, v-vii (2019)
132.
Tetko, I.V. ; Theis, F.J. ; Karpov, P. & Kůrková, V.*: Preface. Lect. Notes Comput. Sc. 11729 LNCS, v-vii (2019)
133.
Tetko, I.V. ; Karpov, P. ; Bruno, E.* ; Kimber, T.B.* & Godin, G.*: Augmentation is what you need! Lect. Notes Comput. Sc. 11731 LNCS, 831-835 (2019)
134.
Tetko, I.V. ; Theis, F.J. ; Karpov, P. & Kůrková, V.*: Preface. Lect. Notes Comput. Sc. 11731 LNCS, v-vii (2019)
135.
Waibel, D.J.E. ; Tiemann, U.* ; Lupperger, V. ; Semb, H.* & Marr, C.: In-silico staining from bright-field and fluorescent images using deep learning. In:. 2019. 184-186 (Lect. Notes Comput. Sc. ; 11729 LNCS)
136.
Gutiérrez-Becker, B.* et al.: Deep shape analysis on abdominal organs for diabetes prediction. Lect. Notes Comput. Sc. 11167 LNCS, 223-231 (2018)
137.
Klinger, E. & Hasenauer, J.: A scheme for adaptive selection of population sizes in approximate Bayesian Computation - Sequential Monte Carlo. Lect. Notes Comput. Sc. 10545 LNBI, 128-144 (2017)
138.
Bortsova, G. et al.: Mitosis detection in intestinal crypt images with hough forest and conditional random fields. Lect. Notes Comput. Sc. 10019, 287-295 (2016)
139.
Loos, C. ; Fiedler, A. & Hasenauer, J.: Parameter estimation for reaction rate equation constrained mixture models.  Lect. Notes Comput. Sc. 9859, 186-200 (2016)
140.
Zhou, L.* ; Georgii, E. ; Plant, C.* & Böhm, C.*: Covariate-related structure extraction from paired data. Lect. Notes Comput. Sc. 9832, 151-162 (2016)
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