Lokale Neuronale Filter. - Boris Flach; H. Guth; R. Osterland (DAGM-Symposium, 1992)

Neuronales Sysem zur Objektsegmentierung in der Mikrostrukturvermessung. - Boris Flach; Eeri Kask; R. Osterland (DAGM-Symposium, 1993)

Analog Parallel Algorithms for Computational Geometry. - Frank K. H. A. Dehne; Jörg-Rüdiger Sack; Natana Valiveti; Boris Flach (Parallel Algorithms Appl., 1995)

Objektsegmentierung durch Textur- und Randextraktion. - C. Brock; Boris Flach; Eeri Kask; R. Osterland (DAGM-Symposium, 1996)

A Class of Solvable Consistent Labeling Problems. - Boris Flach; Michail I. Schlesinger (SSPR/SPR, 2000)

Unifying Registration and Segmentation for Multi-sensor Images. - Boris Flach; Eeri Kask; Dmitrij Schlesinger; Andriy Skulish (DAGM-Symposium, 2002)

A Higher Order MRF-Model for Stereo-Reconstruction. - Dmitrij Schlesinger; Boris Flach; Alexander Shekhovtsov (DAGM-Symposium, 2004)

Joint Non-rigid Motion Estimation and Segmentation. - Boris Flach; Radim Sára (IWCIA, 2004)

A Probabilistic Segmentation Scheme. - Dmitrij Schlesinger; Boris Flach (DAGM-Symposium, 2008)

Combining Shape Priors and MRF-Segmentation. - Boris Flach; Dmitrij Schlesinger (SSPR/SPR, 2008)

Modelling composite shapes by Gibbs random fields. - Boris Flach; Dmitrij Schlesinger (CVPR, 2011)

Modelling Distributed Shape Priors by Gibbs Random Fields of Second Order - Boris Flach; Dmitrij Schlesinger (CoRR, 2011)

Unsupervised (parameter) learning for MRFs on bipartite graphs. - Boris Flach; Tomás Sixta (BMVC, 2013)

A Class of Random Fields on Complete Graphs with Tractable Partition Function. - Boris Flach (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

M-best solutions for a class of fuzzy constraint satisfaction problems. - Michail I. Schlesinger; Boris Flach; Evgeniy Vodolazskiy (CoRR, 2014)

Dynamic Programming. - Boris Flach; Václav Hlavác (Computer Vision, A Reference Guide, 2014)

Expectation Maximization Algorithm. - Boris Flach; Václav Hlavác (Computer Vision, A Reference Guide, 2014)

Joint Segmentation and Registration Through the Duality of Congealing and Maximum Likelihood Estimate. - Boris Flach; Archibald Pontier (IPMI, 2015)

Multiple Object Segmentation and Tracking by Bayes Risk Minimization. - Tomás Sixta; Boris Flach (MICCAI (2), 2016)

Generative learning for deep networks. - Boris Flach; Alexander Shekhovtsov; Ondrej Fikar (CoRR, 2017)

Stochastic Normalizations as Bayesian Learning. - Alexander Shekhovtsov; Boris Flach (ACCV (2), 2018)

Normalization of Neural Networks using Analytic Variance Propagation. - Alexander Shekhovtsov; Boris Flach (CoRR, 2018)

Feed-forward Uncertainty Propagation in Belief and Neural Networks. - Alexander Shekhovtsov; Boris Flach; Michal Busta (CoRR, 2018)

Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers. - Alexander Shekhovtsov; Boris Flach (ICLR (Poster), 2019)

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks. - Alexander Shekhovtsov; Viktor Yanush; Boris Flach (NeurIPS, 2020)

Coupling cell detection and tracking by temporal feedback. - Tomás Sixta; Jiahui Cao; Jochen Seebach; Hans Schnittler; Boris Flach (Mach. Vis. Appl., 2020)

VAE Approximation Error: ELBO and Conditional Independence. - Dmitrij Schlesinger; Alexander Shekhovtsov; Boris Flach (CoRR, 2021)

VAE Approximation Error: ELBO and Exponential Families. - Alexander Shekhovtsov; Dmitrij Schlesinger; Boris Flach (ICLR, 2022)

Symmetric Equilibrium Learning of VAEs. - Boris Flach; Dmitrij Schlesinger; Alexander Shekhovtsov (AISTATS, 2024)