Invariant pattern recognition by means of fast synaptic plasticity. - Joachim M. Buhmann; Klaus Schulten (ICNN, 1988)

Neuronale Netzwerke als assoziative Speicher und als Systeme zur Mustererkennung. - Joachim M. Buhmann (1988)

Size and distortion invariant object recognition by hierarchical graph matching. - Joachim M. Buhmann; Martin Lades; Christoph von der Malsburg (IJCNN, 1990)

Pattern Segmentation in Associative Memory. - DeLiang Wang; Joachim M. Buhmann; Christoph von der Malsburg (Neural Comput., 1990)

Complexity Optimized Vector Quantization: A Neutral Network Approach. - Joachim M. Buhmann; Hans Kühnel (Data Compression Conference, 1992)

Sensory segmentation with coupled neural oscillators. - Christoph von der Malsburg; Joachim M. Buhmann (Biol. Cybern., 1992)

Central and Pairwise Data Clustering by Competitive Neural Networks. - Joachim M. Buhmann; Thomas Hofmann 001 (NIPS, 1993)

Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina. - Joachim M. Buhmann; Martin Lades; Frank H. Eeckman (NIPS, 1993)

Complexity Optimized Data Clustering by Competitive Neural Networks. - Joachim M. Buhmann; Hans Kühnel (Neural Comput., 1993)

Distortion Invariant Object Recognition in the Dynamic Link Architecture. - Martin Lades; Jan C. Vorbrüggen; Joachim M. Buhmann; Jörg Lange; Christoph von der Malsburg; Rolf P. Würtz; Wolfgang Konen (IEEE Trans. Computers, 1993)

Vector quantization with complexity costs. - Joachim M. Buhmann; Hans Kühnel (IEEE Trans. Inf. Theory, 1993)

A maximum entropy approach to pairwise data clustering. - Joachim M. Buhmann; Thomas Hofmann 001 (ICPR (2), 1994)

Multidimensional Scaling and Data Clustering. - Thomas Hofmann 001; Joachim M. Buhmann (NIPS, 1994)

The Mobile Robot RHINO. - Joachim M. Buhmann; Wolfram Burgard; Armin B. Cremers; Dieter Fox; Thomas Hofmann 001; Frank E. Schneider; Jiannis Strikos; Sebastian Thrun (AI Mag., 1995)

Komplexe lernende Systeme: der mobile Roboter RHINO. - Armin B. Cremers; Joachim M. Buhmann; Sebastian Thrun (Künstliche Intell., 1995)

An Annealed "Neural Gas" Network for Robust Vector Quantization. - Thomas Hofmann 001; Joachim M. Buhmann (ICANN, 1996)

Unsupervised segmentation of textured images by pairwise data clustering. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (ICIP (3), 1996)

Regularizing phase-based stereo. - Thorsten Fröhlinghaus; Joachim M. Buhmann (ICPR, 1996)

Inferring Hierarchical Clustering Structures by Deterministic Annealing. - Thomas Hofmann 001; Joachim M. Buhmann (KDD, 1996)

Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (CVPR, 1997)

Deterministic Annealing for Unsupervised Texture Segmentation. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (EMMCVPR, 1997)

Multidimensional Scaling by Deterministic Annealing. - Hansjörg Klock; Joachim M. Buhmann (EMMCVPR, 1997)

Robust vector quantization by competitive learning. - Joachim M. Buhmann; Thomas Hofmann 001 (ICASSP, 1997)

An Optimization Approach to Unsupervised Hierarchical Texture Segmentation. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (ICIP (3), 1997)

Region-Based Motion Compensated 3D-Wavelet Transform Coding of Video. - Hansjörg Klock; Andreas Polzer; Joachim M. Buhmann (ICIP (2), 1997)

Video coding by region-based motion compensation and spatio-temporal wavelet transform. - Andreas Polzer; Hansjörg Klock; Joachim M. Buhmann (ICIP (3), 1997)

Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis. - Marcus Held; Joachim M. Buhmann (NIPS, 1997)

Active Data Clustering. - Thomas Hofmann 001; Joachim M. Buhmann (NIPS, 1997)

Pairwise Data Clustering by Deterministic Annealing. - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1997)

Correction to "Pairwise Data Clustering by Deterministic Annealing". - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1997)

Stochastic Algorithms for Exploratory Data Analysis: Data Clustering and Data Visualization. - Joachim M. Buhmann (Learning in Graphical Models, 1998)

Discrete Mixture Models for Unsupervised Image Segmentation. - Jan Puzicha; Joachim M. Buhmann; Thomas Hofmann 001 (DAGM-Symposium, 1998)

On Spatial Quantization of Color Images. - Jens Ketterer; Jan Puzicha; Marcus Held; Martin Fischer 005; Joachim M. Buhmann; Dieter W. Fellner (ECCV (1), 1998)

Multiscale Annealing for Real-Time Unsupervised Texture Segmentation. - Jan Puzicha; Joachim M. Buhmann (ICCV, 1998)

Visualizing Group Structure. - Marcus Held; Jan Puzicha; Joachim M. Buhmann (NIPS, 1998)

Unsupervised Learning for Robust Texture Segmentation. - Joachim M. Buhmann; Jan Puzicha (Theoretical Foundations of Computer Vision, 1998)

Dithered Color Quantization. - Joachim M. Buhmann; Dieter W. Fellner; Marcus Held; Jens Ketterer; Jan Puzicha (Comput. Graph. Forum, 1998)

Knowledge-Discovery: Wie können wir Muster und Strukturen in Daten zuverlässig erkennen? - Joachim M. Buhmann (Künstliche Intell., 1998)

Unsupervised Texture Segmentation in a Deterministic Annealing Framework. - Thomas Hofmann 001; Jan Puzicha; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

Competitive learning algorithms for robust vector quantization. - Thomas Hofmann 001; Joachim M. Buhmann (IEEE Trans. Signal Process., 1998)

Histogram Clustering for Unsupervised Image Segmentation. - Jan Puzicha; Joachim M. Buhmann; Thomas Hofmann 001 (CVPR, 1999)

Model Selection in Clustering by Uniform Convergence Bounds. - Joachim M. Buhmann; Marcus Held (NIPS, 1999)

Multiscale Annealing for Grouping and Unsupervised Texture Segmentation. - Jan Puzicha; Joachim M. Buhmann (Comput. Vis. Image Underst., 1999)

Histogram clustering for unsupervised segmentation and image retrieval. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (Pattern Recognit. Lett., 1999)

On Learning Optimal Texture Edge Detectors. - Stefan Will; Lothar Hermes; Joachim M. Buhmann; Jan Puzicha (ICIP, 2000)

Active Learning for Hierarchical Pairwise Data Clustering. - Joachim M. Buhmann; Thomas Zöller (ICPR, 2000)

Feature Selection for Support Vector Machines. - Lothar Hermes; Joachim M. Buhmann (ICPR, 2000)

Data visualization by multidimensional scaling: a deterministic annealing approach. - Hansjörg Klock; Joachim M. Buhmann (Pattern Recognit., 2000)

A theory of proximity based clustering: structure detection by optimization. - Jan Puzicha; Thomas Hofmann 001; Joachim M. Buhmann (Pattern Recognit., 2000)

On spatial quantization of color images. - Jan Puzicha; Marcus Held; Jens Ketterer; Joachim M. Buhmann; Dieter W. Fellner (IEEE Trans. Image Process., 2000)

Contextual Classification by Entropy-Based Polygonization. - Lothar Hermes; Joachim M. Buhmann (CVPR (2), 2001)

A New Contour-Based Approach to Object Recognition for Assembly Line Robots. - Markus Suing; Lothar Hermes; Joachim M. Buhmann (DAGM-Symposium, 2001)

Path Based Pairwise Data Clustering with Application to Texture Segmentation. - Bernd Fischer 003; Thomas Zöller; Joachim M. Buhmann (EMMCVPR, 2001)

Topology Free Hidden Markov Models: Application to Background Modeling. - Bjoern Stenger; Visvanathan Ramesh; Nikos Paragios; Frans Coetzee; Joachim M. Buhmann (ICCV, 2001)

Coupled Clustering: a Method for Detecting Structural Correspondence. - Zvika Marx; Ido Dagan; Joachim M. Buhmann (ICML, 2001)

The Noisy Euclidean Traveling Salesman Problem and Learning. - Mikio L. Braun; Joachim M. Buhmann (NIPS, 2001)

Empirical Evaluation of Dissimilarity Measures for Color and Texture. - Yossi Rubner; Jan Puzicha; Carlo Tomasi; Joachim M. Buhmann (Comput. Vis. Image Underst., 2001)

A Resampling Approach to Cluster Validation. - Volker Roth 001; Tilman Lange; Mikio L. Braun; Joachim M. Buhmann (COMPSTAT, 2002)

Data Resampling for Path Based Clustering. - Bernd Fischer 003; Joachim M. Buhmann (DAGM-Symposium, 2002)

Parametric Distributional Clustering for Image Segmentation. - Lothar Hermes; Thomas Zöller; Joachim M. Buhmann (ECCV (3), 2002)

Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data. - Volker Roth 001; Mikio L. Braun; Tilman Lange; Joachim M. Buhmann (ICANN, 2002)

Combined Color And Texture Segmentation by Parametric Distributional Clustering. - Thomas Zöller; Lothar Hermes; Joachim M. Buhmann (ICPR (2), 2002)

Stability-Based Model Selection. - Tilman Lange; Mikio L. Braun; Volker Roth 001; Joachim M. Buhmann (NIPS, 2002)

Going Metric: Denoising Pairwise Data. - Volker Roth 001; Julian Laub; Joachim M. Buhmann; Klaus-Robert Müller (NIPS, 2002)

Coupled Clustering: A Method for Detecting Structural Correspondence. - Zvika Marx; Ido Dagan; Joachim M. Buhmann; Eli Shamir 001 (J. Mach. Learn. Res., 2002)

A New Distance Measure for Probabilistic Shape Modeling. - Wei-Jun Chen; Joachim M. Buhmann (DAGM-Symposium, 2003)

Semi-supervised Image Segmentation by Parametric Distributional Clustering. - Lothar Hermes; Joachim M. Buhmann (EMMCVPR, 2003)

A Compositionally Architecture for Perceptual Feature Grouping. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2003)

Clustering with the Connectivity Kernel. - Bernd Fischer 003; Volker Roth 001; Joachim M. Buhmann (NIPS, 2003)

Path-Based Clustering for Grouping of Smooth Curves and Texture Segmentation. - Bernd Fischer 003; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2003)

Bagging for Path-Based Clustering. - Bernd Fischer 003; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2003)

Optimal Cluster Preserving Embedding of Nonmetric Proximity Data. - Volker Roth 001; Julian Laub; Motoaki Kawanabe; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2003)

A minimum entropy approach to adaptive image polygonization. - Lothar Hermes; Joachim M. Buhmann (IEEE Trans. Image Process., 2003)

Shape Constrained Image Segmentation by Parametric Distributional Clustering. - Thomas Zöller; Joachim M. Buhmann (CVPR (1), 2004)

Landscape of Clustering Algorithms. - Anil K. Jain 001; Alexander P. Topchy; Martin H. C. Law; Joachim M. Buhmann (ICPR (1), 2004)

A Hidden Markov Model for de Novo Peptide Sequencing. - Bernd Fischer 003; Volker Roth 001; Joachim M. Buhmann; Jonas Grossmann; Sacha Baginsky; Wilhelm Gruissem; Franz F. Roos; Peter Widmayer (NIPS, 2004)

Clustering in Computer Vision and Data Analysis. - Joachim M. Buhmann (PRIS, 2004)

Stability-Based Validation of Clustering Solutions. - Tilman Lange; Volker Roth 001; Mikio L. Braun; Joachim M. Buhmann (Neural Comput., 2004)

Boundary-constrained agglomerative segmentation. - Lothar Hermes; Joachim M. Buhmann (IEEE Trans. Geosci. Remote. Sens., 2004)

Learning with Constrained and Unlabelled Data. - Tilman Lange; Martin H. C. Law; Anil K. Jain 001; Joachim M. Buhmann (CVPR (1), 2005)

Object Categorization by Compositional Graphical Models. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2005)

SAR images as mixtures of Gaussian mixtures. - Peter Orbanz; Joachim M. Buhmann (ICIP (2), 2005)

Combining partitions by probabilistic label aggregation. - Tilman Lange; Joachim M. Buhmann (KDD, 2005)

Fusion of Similarity Data in Clustering. - Tilman Lange; Joachim M. Buhmann (NIPS, 2005)

Image Segmentation by Networks of Spiking Neurons. - Joachim M. Buhmann; Tilman Lange; Ulrich Ramacher (Neural Comput., 2005)

Learning Top-Down Grouping of Compositional Hierarchies for Recognition. - Björn Ommer; Michael Sauter; Joachim M. Buhmann (CVPR Workshops, 2006)

Model Order Selection and Cue Combination for Image Segmentation. - Andrew Rabinovich; Serge J. Belongie; Tilman Lange; Joachim M. Buhmann (CVPR (1), 2006)

Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information. - Mikio L. Braun; Tilman Lange; Joachim M. Buhmann (DAGM-Symposium, 2006)

Probabilistic De Novo Peptide Sequencing with Doubly Charged Ions. - Hansruedi Peter; Bernd Fischer 003; Joachim M. Buhmann (DAGM-Symposium, 2006)

Dense Stereo by Triangular Meshing and Cross Validation. - Peter Wey; Bernd Fischer 003; Herbert Bay; Joachim M. Buhmann (DAGM-Symposium, 2006)

Learning Compositional Categorization Models. - Björn Ommer; Joachim M. Buhmann (ECCV (3), 2006)

Smooth Image Segmentation by Nonparametric Bayesian Inference. - Peter Orbanz; Joachim M. Buhmann (ECCV (1), 2006)

PerformancePrediction Challenge. - Isabelle Guyon; Amir Reza Saffari Azar Alamdari; Gideon Dror; Joachim M. Buhmann (IJCNN, 2006)

Semi-supervised LC/MS alignment for differential proteomics. - Bernd Fischer 003; Jonas Grossmann; Volker Roth 001; Wilhelm Gruissem; Sacha Baginsky; Joachim M. Buhmann (ISMB (Supplement of Bioinformatics), 2006)

Denoising and Dimension Reduction in Feature Space. - Mikio L. Braun; Joachim M. Buhmann; Klaus-Robert Müller (NIPS, 2006)

On the information and representation of non-Euclidean pairwise data. - Julian Laub; Volker Roth 001; Joachim M. Buhmann; Klaus-Robert Müller (Pattern Recognit., 2006)

Learning the Compositional Nature of Visual Objects. - Björn Ommer; Joachim M. Buhmann (CVPR, 2007)

Regularized Data Fusion Improves Image Segmentation. - Tilman Lange; Joachim M. Buhmann (DAGM-Symposium, 2007)

Kernel-Based Grouping of Histogram Data. - Tilman Lange; Joachim M. Buhmann (ECML, 2007)

Compositional Object Recognition, Segmentation, and Tracking in Video. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2007)

Bayesian Order-Adaptive Clustering for Video Segmentation. - Peter Orbanz; Samuel Braendle; Joachim M. Buhmann (EMMCVPR, 2007)

Cluster analysis of heterogeneous rank data. - Ludwig M. Busse; Peter Orbanz; Joachim M. Buhmann (ICML, 2007)

Complex Statistical Models for Object Recognition and Mass Spectrometry. - Joachim M. Buhmann (PRIS, 2007)

PepSplice: cache-efficient search algorithms for comprehensive identification of tandem mass spectra. - Franz F. Roos; Riko Jacob; Jonas Grossmann; Bernd Fischer 003; Joachim M. Buhmann; Wilhelm Gruissem; Sacha Baginsky; Peter Widmayer (Bioinform., 2007)

Time-series alignment by non-negative multiple generalized canonical correlation analysis. - Bernd Fischer 003; Volker Roth 001; Joachim M. Buhmann (BMC Bioinform., 2007)

Robust Image Segmentation Using Resampling and Shape Constraints. - Thomas Zöller; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2007)

A class of probabilistic models for role engineering. - Mario Frank 001; David A. Basin; Joachim M. Buhmann (CCS, 2008)

Probabilistic image registration and anomaly detection by nonlinear warping. - Verena Kaynig; Bernd Fischer 003; Joachim M. Buhmann (CVPR, 2008)

Weakly Supervised Cell Nuclei Detection and Segmentation on Tissue Microarrays of Renal Clear Cell Carcinoma. - Thomas J. Fuchs; Tilman Lange; Peter J. Wild; Holger Moch; Joachim M. Buhmann (DAGM-Symposium, 2008)

Automatic Detection of Learnability under Unreliable and Sparse User Feedback. - Yvonne Moh; Wolfgang Einhäuser; Joachim M. Buhmann (DAGM-Symposium, 2008)

Music preference learning with partial information. - Yvonne Moh; Peter Orbanz; Joachim M. Buhmann (ICASSP, 2008)

Expectation-maximization for sparse and non-negative PCA. - Christian D. Sigg; Joachim M. Buhmann (ICML, 2008)

Kernel Expansion for Online Preference Tracking. - Yvonne Moh; Joachim M. Buhmann (ISMIR, 2008)

Computational Pathology Analysis of Tissue Microarrays Predicts Survival of Renal Clear Cell Carcinoma Patients. - Thomas J. Fuchs; Peter J. Wild; Holger Moch; Joachim M. Buhmann (MICCAI (2), 2008)

Classification of Multi-labeled Data: A Generative Approach. - Andreas P. Streich; Joachim M. Buhmann (ECML/PKDD (2), 2008)

Nonparametric Bayesian Image Segmentation. - Peter Orbanz; Joachim M. Buhmann (Int. J. Comput. Vis., 2008)

On Relevant Dimensions in Kernel Feature Spaces. - Mikio L. Braun; Joachim M. Buhmann; Klaus-Robert Müller (J. Mach. Learn. Res., 2008)

A probabilistic approach to hybrid role mining. - Mario Frank 001; Andreas P. Streich; David A. Basin; Joachim M. Buhmann (CCS, 2009)

Stable Bayesian Parameter Estimation for Biological Dynamical Systems. - Alberto Giovanni Busetto; Joachim M. Buhmann (CSE (1), 2009)

Manifold regularization for semi-supervised sequential learning. - Yvonne Moh; Joachim M. Buhmann (ICASSP, 2009)

Inter-active learning of randomized tree ensembles for object detection. - Thomas J. Fuchs; Joachim M. Buhmann (ICCV Workshops, 2009)

Optimized expected information gain for nonlinear dynamical systems. - Alberto Giovanni Busetto; Cheng Soon Ong; Joachim M. Buhmann (ICML, 2009)

Randomized Tree Ensembles for Object Detection in Computational Pathology. - Thomas J. Fuchs; Johannes Haybaeck; Peter J. Wild; Mathias Heikenwalder; Holger Moch; Adriano Aguzzi; Joachim M. Buhmann (ISVC (1), 2009)

Graph-Based Pancreatic Islet Segmentation for Early Type 2 Diabetes Mellitus on Histopathological Tissue. - Xenofon E. Floros; Thomas J. Fuchs; Markus P. Rechsteiner; Giatgen Spinas; Holger Moch; Joachim M. Buhmann (MICCAI (1), 2009)

Adaptive bandwidth selection for biomarker discovery in mass spectrometry. - Bernd Fischer 003; Volker Roth 001; Joachim M. Buhmann (Artif. Intell. Medicine, 2009)

Proteome coverage prediction with infinite Markov models. - Manfred Claassen; Ruedi Aebersold; Joachim M. Buhmann (Bioinform., 2009)

Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. - Björn Ommer; Theodor Mader; Joachim M. Buhmann (Int. J. Comput. Vis., 2009)

Structure Identification by Optimized Interventions. - Alberto Giovanni Busetto; Joachim M. Buhmann (AISTATS, 2009)

Spanning Tree Approximations for Conditional Random Fields. - Patrick Pletscher; Cheng Soon Ong; Joachim M. Buhmann (AISTATS, 2009)

Neuron geometry extraction by perceptual grouping in ssTEM images. - Verena Kaynig; Thomas J. Fuchs; Joachim M. Buhmann (CVPR, 2010)

Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning. - Alexander Vezhnevets; Joachim M. Buhmann (CVPR, 2010)

Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (DAGM-Symposium, 2010)

Regularized online learning of pseudometrics. - Yvonne Moh; Joachim M. Buhmann (ICASSP, 2010)

Speech enhancement with sparse coding in learned dictionaries. - Christian D. Sigg; Tomas Dikk; Joachim M. Buhmann (ICASSP, 2010)

The Balanced Accuracy and Its Posterior Distribution. - Kay Henning Brodersen; Cheng Soon Ong; Klaas Enno Stephan; Joachim M. Buhmann (ICPR, 2010)

The Binormal Assumption on Precision-Recall Curves. - Kay Henning Brodersen; Cheng Soon Ong; Klaas Enno Stephan; Joachim M. Buhmann (ICPR, 2010)

Information theoretic model validation for clustering. - Joachim M. Buhmann (ISIT, 2010)

Geometrical Consistent 3D Tracing of Neuronal Processes in ssTEM Data. - Verena Kaynig; Thomas J. Fuchs; Joachim M. Buhmann (MICCAI (2), 2010)

Entropy and Margin Maximization for Structured Output Learning. - Patrick Pletscher; Cheng Soon Ong; Joachim M. Buhmann (ECML/PKDD (3), 2010)

On the definition of role mining. - Mario Frank 001; Joachim M. Buhmann; David A. Basin (SACMAT, 2010)

Infinite mixture-of-experts model for sparse survival regression with application to breast cancer. - Sudhir Raman; Thomas J. Fuchs; Peter J. Wild; Edgar Dahl; Joachim M. Buhmann; Volker Roth 001 (BMC Bioinform., 2010)

Learning the Compositional Nature of Visual Object Categories for Recognition. - Björn Ommer; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Modeling Engagement Dynamics in Spelling Learning. - Gian-Marco Baschera; Alberto Giovanni Busetto; Severin Klingler; Joachim M. Buhmann; Markus H. Gross (AIED, 2011)

Agnostic Domain Adaptation. - Alexander Vezhnevets; Joachim M. Buhmann (DAGM-Symposium, 2011)

Predicting Graduate-level Performance from Undergraduate Achievements. - Judith Zimmermann; Kay Henning Brodersen; Jean-Philippe Pellet; Elias August; Joachim M. Buhmann (EDM, 2011)

Weakly supervised semantic segmentation with a multi-image model. - Alexander Vezhnevets; Vittorio Ferrari; Joachim M. Buhmann (ICCV, 2011)

Selecting the rank of truncated SVD by maximum approximation capacity. - Mario Frank 001; Joachim M. Buhmann (ISIT, 2011)

Context Sensitive Information: Model Validation by Information Theory. - Joachim M. Buhmann (MCPR, 2011)

The Minimum Transfer Cost Principle for Model-Order Selection. - Mario Frank 001; Morteza Haghir Chehreghani; Joachim M. Buhmann (ECML/PKDD (1), 2011)

Model-Based Clustering of Inhomogeneous Paired Comparison Data. - Ludwig M. Busse; Joachim M. Buhmann (SIMBAD, 2011)

Computational pathology: Challenges and promises for tissue analysis. - Thomas J. Fuchs; Joachim M. Buhmann (Comput. Medical Imaging Graph., 2011)

Selecting the rank of SVD by Maximum Approximation Capacity - Mario Frank 001; Joachim M. Buhmann (CoRR, 2011)

Proteome Coverage Prediction for Integrated Proteomics Datasets. - Manfred Claassen; Ruedi Aebersold; Joachim M. Buhmann (J. Comput. Biol., 2011)

Model-based feature construction for multivariate decoding. - Kay Henning Brodersen; Florent Haiss; Cheng Soon Ong; Fabienne Jung; Marc Tittgemeyer; Joachim M. Buhmann; Bruno Weber; Klaas E. Stephan (NeuroImage, 2011)

Generative Embedding for Model-Based Classification of fMRI Data. - Kay Henning Brodersen; Thomas M. Schofield; Alexander P. Leff; Cheng Soon Ong; Ekaterina I. Lomakina; Joachim M. Buhmann; Klaas E. Stephan (PLoS Comput. Biol., 2011)

Active learning for semantic segmentation with expected change. - Alexander Vezhnevets; Joachim M. Buhmann; Vittorio Ferrari (CVPR, 2012)

Weakly supervised structured output learning for semantic segmentation. - Alexander Vezhnevets; Vittorio Ferrari; Joachim M. Buhmann (CVPR, 2012)

Computational modeling for assessment of IBD: To be or not to be? - Franciscus M. Vos; Jeroen A. W. Tielbeek; Robiel E. Naziroglu; Zhang Li; Peter Schueffler; Dwarikanath Mahapatra; Alexander Wiebel; Cristina Lavini; Joachim M. Buhmann; Hans-Christian Hege; Jaap Stoker; Lucas J. van Vliet (EMBC, 2012)

The information content in sorting algorithms. - Ludwig M. Busse; Morteza Haghir Chehreghani; Joachim M. Buhmann (ISIT, 2012)

Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections. - Dmitry Laptev; Alexander Vezhnevets; Sarvesh Dwivedi; Joachim M. Buhmann (MICCAI (1), 2012)

Cardiac LV and RV Segmentation Using Mutual Context Information. - Dwarikanath Mahapatra; Joachim M. Buhmann (MLMI, 2012)

A Supervised Learning Based Approach to Detect Crohn's Disease in Abdominal MR Volumes. - Dwarikanath Mahapatra; Peter Schueffler; Jeroen A. W. Tielbeek; Joachim M. Buhmann; Franciscus M. Vos (Abdominal Imaging, 2012)

Bayesian mixed-effects inference on classification performance in hierarchical data sets. - Kay Henning Brodersen; Christoph Mathys; Justin R. Chumbley; Jean Daunizeau; Cheng Soon Ong; Joachim M. Buhmann; Klaas E. Stephan (J. Mach. Learn. Res., 2012)

Information Theoretic Model Selection for Pattern Analysis. - Joachim M. Buhmann; Morteza Haghir Chehreghani; Mario Frank 001; Andreas P. Streich (ICML Unsupervised and Transfer Learning, 2012)

Information Theoretic Model Validation for Spectral Clustering. - Morteza Haghir Chehreghani; Alberto Giovanni Busetto; Joachim M. Buhmann (AISTATS, 2012)

Multi-Assignment Clustering for Boolean Data. - Mario Frank 001; Andreas P. Streich; David A. Basin; Joachim M. Buhmann (J. Mach. Learn. Res., 2012)

Decoding the perception of pain from fMRI using multivariate pattern analysis. - Kay Henning Brodersen; Katja Wiech; Ekaterina I. Lomakina; Chia-shu Lin; Joachim M. Buhmann; Ulrike Bingel; Markus Ploner; Klaas Enno Stephan; Irene Tracey (NeuroImage, 2012)

Learning Dictionaries With Bounded Self-Coherence. - Christian D. Sigg; Tomas Dikk; Joachim M. Buhmann (IEEE Signal Process. Lett., 2012)

Speech Enhancement Using Generative Dictionary Learning. - Christian D. Sigg; Tomas Dikk; Joachim M. Buhmann (IEEE Trans. Speech Audio Process., 2012)

Approximate Sorting. - Ludwig M. Busse; Morteza Haghir Chehreghani; Joachim M. Buhmann (GCPR, 2013)

Ellipsoidal Multiple Instance Learning. - Gabriel Krummenacher; Cheng Soon Ong; Joachim M. Buhmann (ICML (2), 2013)

Robust optimization in the presence of uncertainty. - Joachim M. Buhmann; Matús Mihalák; Rastislav Srámek; Peter Widmayer (ITCS, 2013)

Automatic cardiac RV segmentation using semantic information with graph cuts. - Dwarikanath Mahapatra; Joachim M. Buhmann (ISBI, 2013)

Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2013)

Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI. - Dwarikanath Mahapatra; Alexander Vezhnevets; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2013)

Semi-Supervised and Active Learning for Automatic Segmentation of Crohn's Disease. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (MICCAI (2), 2013)

A Model Development Pipeline for Crohn's Disease Severity Assessment from Magnetic Resonance Images. - Peter J. Schüffler; Dwarikanath Mahapatra; Jeroen A. W. Tielbeek; Franciscus M. Vos; Jesica Makanyanga; Doug Pendsé; C. Yung Nio; Jaap Stoker; Stuart A. Taylor; Joachim M. Buhmann (Abdominal Imaging, 2013)

Localizing and segmenting Crohn's disease affected regions in abdominal MRI using novel context features. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (Image Processing, 2013)

Correlated random features for fast semi-supervised learning. - Brian McWilliams; David Balduzzi; Joachim M. Buhmann (NIPS, 2013)

Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains. - Tanja Käser; Gian-Marco Baschera; Alberto Giovanni Busetto; Severin Klingler; Barbara Solenthaler; Joachim M. Buhmann; Markus H. Gross (Int. J. Artif. Intell. Educ., 2013)

Near-optimal experimental design for model selection in systems biology. - Alberto Giovanni Busetto; Alain Hauser; Gabriel Krummenacher; Mikael Sunnåker; Sotiris Dimopoulos; Cheng Soon Ong; Jörg Stelling; Joachim M. Buhmann (Bioinform., 2013)

A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure. - Dwarikanath Mahapatra; Peter Schueffler; Jeroen A. W. Tielbeek; Joachim M. Buhmann; Franciscus M. Vos (J. Digit. Imaging, 2013)

Variational Bayesian mixed-effects inference for classification studies. - Kay Henning Brodersen; Jean Daunizeau; Christoph Mathys; Justin R. Chumbley; Joachim M. Buhmann; Klaas E. Stephan (NeuroImage, 2013)

Role Mining with Probabilistic Models. - Mario Frank 001; Joachim M. Buhmann; David A. Basin (ACM Trans. Inf. Syst. Secur., 2013)

Automatic Detection and Segmentation of Crohn's Disease Tissues From Abdominal MRI. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Jesica Makanyanga; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (IEEE Trans. Medical Imaging, 2013)

SIMBAD: Emergence of Pattern Similarity. - Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Structure Preserving Embedding of Dissimilarity Data. - Volker Roth 001; Thomas J. Fuchs; Julia E. Vogt; Sandhya Prabhakaran; Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Convolutional Decision Trees for Feature Learning and Segmentation. - Dmitry Laptev; Joachim M. Buhmann (GCPR, 2014)

SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data. - Dmitry Laptev; Joachim M. Buhmann (Neural Connectomics, 2014)

Superslicing frame restoration for anisotropic sstem. - Dmitry Laptev; A. Veznevets; Joachim M. Buhmann (ISBI, 2014)

Active learning based segmentation of Crohn's disease using principles of visual saliency. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Jesica Makanyanga; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2014)

How informative are Minimum Spanning Tree algorithms? - Alexey Gronskiy; Joachim M. Buhmann (ISIT, 2014)

Sparse feature selection by information theory. - Guangyao Zhou; Stuart Geman; Joachim M. Buhmann (ISIT, 2014)

Combining Multiple Expert Annotations Using Semi-supervised Learning and Graph Cuts for Crohn's Disease Segmentation. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Carl A. J. Puylaert; Jesica C. Makanyanga; Alex Menys; Rado Andriantsimiavona; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (ABDI@MICCAI, 2014)

Semi-automatic Crohn's Disease Severity Estimation on MR Imaging. - Peter J. Schüffler; Dwarikanath Mahapatra; Robiel Naziroglu; Zhang Li; Carl A. J. Puylaert; Rado Andriantsimiavona; Franciscus M. Vos; Doug A. Pendsé; C. Yung Nio; Jaap Stoker; Stuart A. Taylor; Joachim M. Buhmann (ABDI@MICCAI, 2014)

Fast and Robust Least Squares Estimation in Corrupted Linear Models. - Brian McWilliams; Gabriel Krummenacher; Mario Lucic; Joachim M. Buhmann (NIPS, 2014)

Prostate MRI Segmentation Using Learned Semantic Knowledge and Graph Cuts. - Dwarikanath Mahapatra; Joachim M. Buhmann (IEEE Trans. Biomed. Eng., 2014)

Kickback Cuts Backprop's Red-Tape: Biologically Plausible Credit Assignment in Neural Networks. - David Balduzzi; Hastagiri Vanchinathan; Joachim M. Buhmann (AAAI, 2015)

Transformation-Invariant Convolutional Jungles. - Dmitry Laptev; Joachim M. Buhmann (CVPR, 2015)

A field of experts model for optic cup and disc segmentation from retinal fundus images. - Dwarikanath Mahapatra; Joachim M. Buhmann (ISBI, 2015)

Joint segmentation and groupwise registration of cardiac DCE MRI using sparse data representations. - Dwarikanath Mahapatra; Zhang Li; Frans Vos; Joachim M. Buhmann (ISBI, 2015)

Crohn's disease segmentation from MRI using learned image priors. - Dwarikanath Mahapatra; Peter J. Schüffler; Frans Vos; Joachim M. Buhmann (ISBI, 2015)

Greedy MaxCut algorithms and their information content. - Yatao Bian; Alexey Gronskiy; Joachim M. Buhmann (ITW, 2015)

Visual Saliency Based Active Learning for Prostate MRI Segmentation. - Dwarikanath Mahapatra; Joachim M. Buhmann (MLMI, 2015)

Boosting Convolutional Filters with Entropy Sampling for Optic Cup and Disc Image Segmentation from Fundus Images. - Julian G. Zilly; Joachim M. Buhmann; Dwarikanath Mahapatra (MLMI, 2015)

Asymptotic analysis of estimators on multi-label data. - Andreas P. Streich; Joachim M. Buhmann (Mach. Learn., 2015)

Inversion of hierarchical Bayesian models using Gaussian processes. - Ekaterina I. Lomakina; Saee Paliwal; Andreea Oliviana Diaconescu; Kay Henning Brodersen; Eduardo A. Aponte; Joachim M. Buhmann; Klaas E. Stephan (NeuroImage, 2015)

TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks. - Dmitry Laptev; Nikolay Savinov; Joachim M. Buhmann; Marc Pollefeys (CVPR, 2016)

Information-theoretic analysis of MaxCut algorithms. - Yatao Bian; Alexey Gronskiy; Joachim M. Buhmann (ITA, 2016)

Scalable Adaptive Stochastic Optimization Using Random Projections. - Gabriel Krummenacher; Brian McWilliams; Yannic Kilcher; Joachim M. Buhmann; Nicolai Meinshausen (NIPS, 2016)

Active learning based segmentation of Crohns disease from abdominal MRI. - Dwarikanath Mahapatra; Franciscus M. Vos; Joachim M. Buhmann (Comput. Methods Programs Biomed., 2016)

Multi-Organ Cancer Classification and Survival Analysis. - Stefan Bauer; Nicolas Carion; Peter J. Schüffler; Thomas J. Fuchs; Peter J. Wild; Joachim M. Buhmann (CoRR, 2016)

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. - Andrew An Bian; Baharan Mirzasoleiman; Joachim M. Buhmann; Andreas Krause 001 (AISTATS, 2017)

Phase Transitions in Parameter Rich Optimization Problems. - Joachim M. Buhmann; Julien Dumazert; Alexey Gronskiy; Wojciech Szpankowski (ANALCO, 2017)

Model Selection for Gaussian Process Regression. - Nico S. Gorbach; Andrew An Bian; Benjamin Fischer; Stefan Bauer; Joachim M. Buhmann (GCPR, 2017)

Guarantees for Greedy Maximization of Non-submodular Functions with Applications. - Andrew An Bian; Joachim M. Buhmann; Andreas Krause 001; Sebastian Tschiatschek (ICML, 2017)

MRI-Based Surgical Planning for Lumbar Spinal Stenosis. - Gabriele Abbati; Stefan Bauer; Sebastian Winklhofer; Peter J. Schüffler; Ulrike Held; Jakob M. Burgstaller; Johann Steurer; Joachim M. Buhmann (MICCAI (3), 2017)

Efficient and Flexible Inference for Stochastic Systems. - Stefan Bauer; Nico S. Gorbach; Ðorðe Miladinovic; Joachim M. Buhmann (NIPS, 2017)

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. - An Bian; Kfir Yehuda Levy; Andreas Krause 001; Joachim M. Buhmann (NIPS, 2017)

Scalable Variational Inference for Dynamical Systems. - Nico S. Gorbach; Stefan Bauer; Joachim M. Buhmann (NIPS, 2017)

Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation. - Julian G. Zilly; Joachim M. Buhmann; Dwarikanath Mahapatra (Comput. Medical Imaging Graph., 2017)

Regression DCM for fMRI. - Stefan Frässle; Ekaterina I. Lomakina; Adeel Razi; Karl J. Friston; Joachim M. Buhmann; Klaas E. Stephan (NeuroImage, 2017)

VIS Capstone Address : Can I believe what I see?-Information theoretic algorithm validation. - Joachim M. Buhmann (VAST, 2018)

Data-driven fiber tractography with neural networks. - Viktor Wegmayr; Giacomo Giuliari; Stefan Holdener; Joachim M. Buhmann (ISBI, 2018)

Free Energy Asymptotics for Problems with Weak Solution Dependencies. - Alexey Gronskiy; Joachim M. Buhmann; Wojciech Szpankowski (ISIT, 2018)

Classification of brain MRI with big data and deep 3D convolutional neural networks. - Viktor Wegmayr; Sai Aitharaju; Joachim M. Buhmann (Computer-Aided Diagnosis, 2018)

Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference. - An Bian; Joachim M. Buhmann; Andreas Krause 001 (CoRR, 2018)

Robust optimization in the presence of uncertainty: A generic approach. - Joachim M. Buhmann; Alexey Gronskiy; Matús Mihalák; Tobias Pröger; Rastislav Srámek; Peter Widmayer (J. Comput. Syst. Sci., 2018)

A generative model of whole-brain effective connectivity. - Stefan Frässle; Ekaterina I. Lomakina; Lars Kasper; Zina M. Manjaly; Alexander P. Leff; Klaas P. Pruessmann; Joachim M. Buhmann; Klaas E. Stephan (NeuroImage, 2018)

Pipeline validation for connectivity-based cortex parcellation. - Nico S. Gorbach; Marc Tittgemeyer; Joachim M. Buhmann (NeuroImage, 2018)

Posterior agreement for large parameter-rich optimization problems. - Joachim M. Buhmann; Julien Dumazert; Alexey Gronskiy; Wojciech Szpankowski (Theor. Comput. Sci., 2018)

Wheel Defect Detection With Machine Learning. - Gabriel Krummenacher; Cheng Soon Ong; Stefan Koller; Seijin Kobayashi; Joachim M. Buhmann (IEEE Trans. Intell. Transp. Syst., 2018)

Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization. - Luca Corinzia; Jesse Provost; Alessandro Candreva; Maurizio Tamarasso; Francesco Maisano; Joachim M. Buhmann (AIME, 2019)

Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. - Philippe Wenk; Alkis Gotovos; Stefan Bauer; Nico S. Gorbach; Andreas Krause 001; Joachim M. Buhmann (AISTATS, 2019)

Entrack: A Data-Driven Maximum-Entropy Approach to Fiber Tractography. - Viktor Wegmayr; Giacomo Giuliari; Joachim M. Buhmann (GCPR, 2019)

Generative Aging of Brain MR-Images and Prediction of Alzheimer Progression. - Viktor Wegmayr; Maurice Hörold; Joachim M. Buhmann (GCPR, 2019)

Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. - Ðorðe Miladinovic; Muhammad Waleed Gondal; Bernhard Schölkopf; Joachim M. Buhmann; Stefan Bauer (DGS@ICLR, 2019)

Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. - Yatao An Bian; Joachim M. Buhmann; Andreas Krause 001 (ICML, 2019)

Generative Aging Of Brain MRI For Early Prediction Of MCI-AD Conversion. - Viktor Wegmayr; Maurice Hörold; Joachim M. Buhmann (ISBI, 2019)

Exact Recovery for a Family of Community-Detection Generative Models. - Luca Corinzia; Paolo Penna; Luca Mondada; Joachim M. Buhmann (ISIT, 2019)

Disentangled State Space Representations. - Ðorðe Miladinovic; Muhammad Waleed Gondal; Bernhard Schölkopf; Joachim M. Buhmann; Stefan Bauer (CoRR, 2019)

Variational Federated Multi-Task Learning. - Luca Corinzia; Joachim M. Buhmann (CoRR, 2019)

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. - Ðorðe Miladinovic; Christine Muheim; Stefan Bauer; Andrea Spinnler; Daniela Noain; Mojtaba Bandarabadi; Benjamin Gallusser; Gabriel Krummenacher; Christian R. Baumann; Antoine Adamantidis; Steven A. Brown; Joachim M. Buhmann (PLoS Comput. Biol., 2019)

Learning Counterfactual Representations for Estimating Individual Dose-Response Curves. - Patrick Schwab; Lorenz Linhardt; Stefan Bauer; Joachim M. Buhmann; Walter Karlen (AAAI, 2020)

From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. - Aytunc Sahin; Yatao Bian; Joachim M. Buhmann; Andreas Krause 001 (ICML, 2020)

DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds. - Fabian Laumer; Gabriel Fringeli; Alina Dubatovka; Laura Manduchi; Joachim M. Buhmann (ML4H@NeurIPS, 2020)

Instance Segmentation for the Quantification of Microplastic Fiber Images. - Viktor Wegmayr; Aytunc Sahin; Björn Sæmundsson; Joachim M. Buhmann (WACV, 2020)

Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography. - Luca Corinzia; Fabian Laumer; Alessandro Candreva; Maurizio Taramasso; Francesco Maisano; Joachim M. Buhmann (Artif. Intell. Medicine, 2020)

Continuous Submodular Function Maximization. - Yatao Bian; Joachim M. Buhmann; Andreas Krause 001 (CoRR, 2020)

Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. - Ðorðe Miladinovic; Aleksandar Stanic; Stefan Bauer; Jürgen Schmidhuber; Joachim M. Buhmann (ICLR, 2021)

On maximum-likelihood estimation in the all-or-nothing regime. - Luca Corinzia; Paolo Penna; Wojciech Szpankowski; Joachim M. Buhmann (ISIT, 2021)

Self-supervised representation learning for surgical activity recognition. - Daniel Paysan; Luis Haug; Michael Bajka; Markus Oelhafen; Joachim M. Buhmann (Int. J. Comput. Assist. Radiol. Surg., 2021)

Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation. - João B. S. Carvalho; João A. Santinha; Djordje Miladinovic; Joachim M. Buhmann (CoRR, 2021)

Entrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography. - Viktor Wegmayr; Joachim M. Buhmann (Int. J. Comput. Vis., 2021)

Statistical and computational thresholds for the planted k-densest sub-hypergraph problem. - Luca Corinzia; Paolo Penna; Wojciech Szpankowski; Joachim M. Buhmann (AISTATS, 2022)

Holistic Modeling In Medical Image Segmentation Using Spatial Recurrence. - João B. S. Carvalho; João A. Santinha; Djordje Miladinovic; Carlos Cotrini; Joachim M. Buhmann (MIDL, 2022)

Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings. - Lukas Klein; João B. S. Carvalho; Mennatallah El-Assady; Paolo Penna; Joachim M. Buhmann; Paul F. Jaeger (MIDL, 2022)

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. - Djordje Miladinovic; Kumar Shridhar; Kushal Jain; Max B. Paulus; Joachim M. Buhmann; Carl Allen (NeurIPS, 2022)

Learning Long-Term Crop Management Strategies with CyclesGym. - Matteo Turchetta; Luca Corinzia; Scott Sussex; Amanda Burton; Juan Herrera; Ioannis Athanasiadis; Joachim M. Buhmann; Andreas Krause 001 (NeurIPS, 2022)

Gated Domain Units for Multi-source Domain Generalization. - Simon Föll; Alina Dubatovka; Eugen Ernst; Martin Maritsch; Patrik Okanovic; Gudrun Thäter; Joachim M. Buhmann; Felix Wortmann; Krikamol Muandet (CoRR, 2022)

BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning. - Eugene Bykovets; Yannick Metz; Mennatallah El-Assady; Daniel A. Keim; Joachim M. Buhmann (CoRR, 2022)

How to Enable Uncertainty Estimation in Proximal Policy Optimization. - Eugene Bykovets; Yannick Metz; Mennatallah El-Assady; Daniel A. Keim; Joachim M. Buhmann (CoRR, 2022)

Domain Generalization for Diagnosis of Pulmonary Fibrosis Using Dose-Invariant Feature Selection. - João B. S. Carvalho; Carlos Cotrini; Fabian Laumer; André Euler; Katharina Martini; Thomas Frauenfelder; Joachim M. Buhmann (ISBI, 2023)

Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective. - João B. S. Carvalho; Mengtao Zhang; Robin Geyer 002; Carlos Cotrini; Joachim M. Buhmann (NeurIPS, 2023)

Explore In-Context Learning for 3D Point Cloud Understanding. - Zhongbin Fang; Xiangtai Li; Xia Li 005; Joachim M. Buhmann; Chen Change Loy; Mengyuan Liu (NeurIPS, 2023)

Regularizing Adversarial Imitation Learning Using Causal Invariance. - Ivan Ovinnikov; Joachim M. Buhmann (CoRR, 2023)

Weakly supervised inference of personalized heart meshes based on echocardiography videos. - Fabian Laumer; Mounir Amrani; Laura Manduchi; Ami Beuret; Lena Rubi; Alina Dubatovka; Christian M. Matter; Joachim M. Buhmann (Medical Image Anal., 2023)

Gated Domain Units for Multi-source Domain Generalization. - Simon Föll; Alina Dubatovka; Eugen Ernst; Siu Lun Chau; Martin Maritsch; Patrik Okanovic; Gudrun Thäter; Joachim M. Buhmann; Felix Wortmann; Krikamol Muandet (Trans. Mach. Learn. Res., 2023)

ChromaX: a fast and scalable breeding program simulator. - Omar G. Younis; Matteo Turchetta; Daniel Ariza Suarez; Steven Yates; Bruno Studer; Ioannis N. Athanasiadis; Andreas Krause 001; Joachim M. Buhmann; Luca Corinzia (Bioinform., 2023)

Neural Graphics Primitives-based Deformable Image Registration for On-the-fly Motion Extraction. - Xia Li 005; Fabian Zhang; Muheng Li; Damien C. Weber; Antony J. Lomax; Joachim M. Buhmann; Ye Zhang (CoRR, 2024)

Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization. - Marc Bartholet; Taehyeon Kim 001; Ami Beuret; Se-Young Yun; Joachim M. Buhmann (CoRR, 2024)

Point-In-Context: Understanding Point Cloud via In-Context Learning. - Mengyuan Liu; Zhongbin Fang; Xia Li 005; Joachim M. Buhmann; Xiangtai Li; Chen Change Loy (CoRR, 2024)

Continuous sPatial-Temporal Deformable Image Registration (CPT-DIR) for motion modelling in radiotherapy: beyond classic voxel-based methods. - Xia Li 005; Muheng Li; Antony J. Lomax; Joachim M. Buhmann; Ye Zhang (CoRR, 2024)

TAMBRIDGE: Bridging Frame-Centered Tracking and 3D Gaussian Splatting for Enhanced SLAM. - Peifeng Jiang; Hong Liu 008; Xia Li 005; Ti Wang; Fabian Zhang; Joachim M. Buhmann (CoRR, 2024)

Gaussian Representation for Deformable Image Registration. - Jihe Li; Fabian Zhang; Xia Li 005; Tianhao Zhang; Ye Zhang; Joachim M. Buhmann (CoRR, 2024)

Breeding Programs Optimization with Reinforcement Learning. - Omar G. Younis; Luca Corinzia; Ioannis N. Athanasiadis; Andreas Krause 001; Joachim M. Buhmann; Matteo Turchetta (CoRR, 2024)

Learning Causally Invariant Reward Functions from Diverse Demonstrations. - Ivan Ovinnikov; Eugene Bykovets; Joachim M. Buhmann (CoRR, 2024)

Measuring Orthogonality in Representations of Generative Models. - Robin C. Geyer; Alessandro Torcinovich; João B. S. Carvalho; Alexander Meyer; Joachim M. Buhmann (Trans. Mach. Learn. Res., 2024)

Fundamentals of Arthroscopic Surgery Training and beyond: a reinforcement learning exploration and benchmark. - Ivan Ovinnikov; Ami Beuret; Flavia Cavaliere; Joachim M. Buhmann (Int. J. Comput. Assist. Radiol. Surg., 2024)

2D echocardiography video to 3D heart shape reconstruction for clinical application. - Fabian Laumer; Lena Rubi; Michael A. Matter; Stefano Buoso; Gabriel Fringeli; François Mach; Frank Ruschitzka; Joachim M. Buhmann; Christian M. Matter (Medical Image Anal., 2025)

Rethinking Robustness in Machine Learning: A Posterior Agreement Approach. - João B. S. Carvalho; Alessandro Torcinovich; Victor Jimenez Rodriguez; Antonio Emanuele Cinà; Carlos Cotrini; Lea Schönherr; Joachim M. Buhmann (CoRR, 2025)