Automated segmentation of synapses in 3D EM data. - Anna Kreshuk; Christoph N. Straehle; Christoph Sommer 002; Ullrich Köthe; Graham Knott; Fred A. Hamprecht (ISBI, 2011)

Ilastik: Interactive learning and segmentation toolkit. - Christoph Sommer 002; Christoph N. Straehle; Ullrich Köthe; Fred A. Hamprecht (ISBI, 2011)

Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. - Christoph N. Straehle; Ullrich Köthe; Graham Knott; Fred A. Hamprecht (MICCAI (1), 2011)

Seeded watershed cut uncertainty estimators for guided interactive segmentation. - Christoph N. Straehle; Ullrich Köthe; Graham Knott; Kevin L. Briggman; Winfried Denk; Fred A. Hamprecht (CVPR, 2012)

Globally Consistent Multi-label Assignment on the Ray Space of 4D Light Fields. - Sven Wanner; Christoph N. Straehle; Bastian Goldluecke (CVPR, 2013)

K-Smallest Spanning Tree Segmentations. - Christoph N. Straehle; Sven Peter; Ullrich Köthe; Fred A. Hamprecht (GCPR, 2013)

Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria. - Christoph N. Straehle; Ullrich Köthe; Fred A. Hamprecht (ICCV, 2013)

Multiple Instance Learning with Response-Optimized Random Forests. - Christoph N. Straehle; Melih Kandemir; Ullrich Köthe; Fred A. Hamprecht (ICPR, 2014)

Interactive segmentation, uncertainty and learning. - Christoph Nikolas Straehle (2014)

Including Multi-feature Interactions and Redundancy for Feature Ranking in Mixed Datasets. - Arvind Kumar Shekar; Tom Bocklisch; Patricia Iglesias Sánchez; Christoph Nikolas Straehle; Emmanuel Müller (ECML/PKDD (1), 2017)

Conditional Flow Variational Autoencoders for Structured Sequence Prediction. - Apratim Bhattacharyya; Michael Hanselmann; Mario Fritz; Bernt Schiele; Christoph-Nikolas Straehle (CoRR, 2019)

Haar Wavelet Based Block Autoregressive Flows for Trajectories. - Apratim Bhattacharyya; Christoph-Nikolas Straehle; Mario Fritz; Bernt Schiele (GCPR, 2020)

Non-cooperative Multi-agent Systems with Exploring Agents. - Jalal Etesami; Christoph-Nikolas Straehle (CoRR, 2020)

Multiagent trajectory models via game theory and implicit layer-based learning. - Philipp Geiger; Christoph Nikolas Straehle (CoRR, 2020)

Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers. - Philipp Geiger; Christoph-Nikolas Straehle (AAAI, 2021)

Learning Normalizing Flow Policies Based on Highway Demonstrations. - Damian Boborzi; Christoph-Nikolas Straehle; Jens S. Buchner; Lars Mikelsons (ITSC, 2021)

Fail-Safe Generative Adversarial Imitation Learning. - Philipp Geiger; Christoph-Nikolas Straehle (CoRR, 2022)

Anomaly Detection using Contrastive Normalizing Flows. - Robert Schmier; Ullrich Köthe; Christoph-Nikolas Straehle (CoRR, 2022)

Fail-Safe Adversarial Generative Imitation Learning. - Philipp Geiger; Christoph-Nikolas Straehle (Trans. Mach. Learn. Res., 2022)

Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data. - Robert Schmier; Ullrich Köthe; Christoph-Nikolas Straehle (Trans. Mach. Learn. Res., 2023)

Imitation learning by state-only distribution matching. - Damian Boborzi; Christoph-Nikolas Straehle; Jens S. Buchner; Lars Mikelsons (Appl. Intell., 2023)

Adaptive Bounding Box Uncertainties via Two-Step Conformal Prediction. - Alexander Timans; Christoph-Nikolas Straehle; Kaspar Sakmann; Eric T. Nalisnick (ECCV (88), 2024)

Max-Rank: Efficient Multiple Testing for Conformal Prediction. - Alexander Timans; Christoph-Nikolas Straehle; Kaspar Sakmann; Christian A. Naesseth; Eric T. Nalisnick (AISTATS, 2025)