Pattern Recognition Combining De-noising and Linear Discriminant Analysis within a Real World Application. - Volker Roth 001; Volker Steinhage; Stefan Schröder; Armin B. Cremers; Dieter Wittmann (CAIP, 1999)

Pattern Recognition Combining Feature- and Pixel-Based Classification Within a Real World Application. - Volker Roth 001; Artur Pogoda de la Vega; Volker Steinhage; Stefan Schröder (DAGM-Symposium, 1999)

Nonlinear Discriminant Analysis Using Kernel Functions. - Volker Roth 001; Volker Steinhage (NIPS, 1999)

Automatisierte Artenbestimmung von Insekten durch Bildanalyse. - Volker Roth 001; Artur Pogoda de la Vega; Volker Steinhage; Stefan Schröder (Künstliche Intell., 2000)

Pairwise Coupling for Machine Recognition of Hand-Printed Japanese Characters. - Volker Roth 001; Koji Tsuda (CVPR (1), 2001)

Probabilistic Discriminative Kernel Classifiers for Multi-class Problems. - Volker Roth 001 (DAGM-Symposium, 2001)

Sparse Kernel Regressors. - Volker Roth 001 (ICANN, 2001)

Kernel methods for regression and classification. - Volker Roth 001 (VDI-Verlag, 2001)

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

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)

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

Feature Selection in Clustering Problems. - Volker Roth 001; Tilman Lange (NIPS, 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)

Adaptive Feature Selection in Image Segmentation. - Volker Roth 001; Tilman Lange (DAGM-Symposium, 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)

Outlier Detection with One-class Kernel Fisher Discriminants. - Volker Roth 001 (NIPS, 2004)

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

Bayesian class discovery in microarray datasets. - Volker Roth 001; Tilman Lange (IEEE Trans. Biomed. Eng., 2004)

The generalized LASSO. - Volker Roth 001 (IEEE Trans. Neural Networks, 2004)

Exploiting Low-Level Image Segmentation for Object Recognition. - Volker Roth 001; Björn Ommer (DAGM-Symposium, 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)

Kernel Fisher Discriminants for Outlier Detection. - Volker Roth 001 (Neural Comput., 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)

The kernelHMM : Learning Kernel Combinations in Structured Output Domains. - Volker Roth 001; Bernd Fischer 003 (DAGM-Symposium, 2007)

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

Improved functional prediction of proteins by learning kernel combinations in multilabel settings. - Volker Roth 001; Bernd Fischer 003 (BMC Bioinform., 2007)

The Group-Lasso for generalized linear models: uniqueness of solutions and efficient algorithms. - Volker Roth 001; Bernd Fischer 003 (ICML, 2008)

Sparse Bayesian Regression for Grouped Variables in Generalized Linear Models. - Sudhir Raman; Volker Roth 001 (DAGM-Symposium, 2009)

The Bayesian group-Lasso for analyzing contingency tables. - Sudhir Raman; Thomas J. Fuchs; Peter J. Wild; Edgar Dahl; Volker Roth 001 (ICML, 2009)

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

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)

The Group-Lasso: l1, INFINITY Regularization versus l1, 2 Regularization. - Julia E. Vogt; Volker Roth 001 (DAGM-Symposium, 2010)

The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data. - Julia E. Vogt; Sandhya Prabhakaran; Thomas J. Fuchs; Volker Roth 001 (ICML, 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)

Deep Sequencing of a Genetically Heterogeneous Sample: Local Haplotype Reconstruction and Read Error Correction. - Osvaldo Zagordi; Lukas Geyrhofer; Volker Roth 001; Niko Beerenwinkel (J. Comput. Biol., 2010)

Bayesian Partitioning of Large-Scale Distance Data. - David Adametz; Volker Roth 001 (NIPS, 2011)

Automatic Model Selection in Archetype Analysis. - Sandhya Prabhakaran; Sudhir Raman; Julia E. Vogt; Volker Roth 001 (DAGM/OAGM Symposium, 2012)

Sparse Point Estimation for Bayesian Regression via Simulated Annealing. - Sudhir Raman; Volker Roth 001 (DAGM/OAGM Symposium, 2012)

Copula Mixture Model for Dependency-seeking Clustering. - Mélanie Rey; Volker Roth 001 (ICML, 2012)

A Complete Analysis of the l_1, p Group-Lasso. - Julia E. Vogt; Volker Roth 001 (ICML, 2012)

Meta-Gaussian Information Bottleneck. - Mélanie Rey; Volker Roth 001 (NIPS, 2012)

Recovering Networks from Distance Data. - Sandhya Prabhakaran; Karin J. Metzner; Alexander Böhm 003; Volker Roth 001 (ACML, 2012)

Probabilistic Inference of Viral Quasispecies Subject to Recombination. - Armin Töpfer; Osvaldo Zagordi; Sandhya Prabhakaran; Volker Roth 001; Eran Halperin; Niko Beerenwinkel (J. Comput. Biol., 2013)

Recovering networks from distance data. - Sandhya Prabhakaran; David Adametz; Karin J. Metzner; Alexander Böhm 003; Volker Roth 001 (Mach. Learn., 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)

Information Bottleneck for Pathway-Centric Gene Expression Analysis. - David Adametz; Mélanie Rey; Volker Roth 001 (GCPR, 2014)

Sparse meta-Gaussian information bottleneck. - Mélanie Rey; Volker Roth 001; Thomas J. Fuchs (ICML, 2014)

Distance-Based Network Recovery under Feature Correlation. - David Adametz; Volker Roth 001 (NIPS, 2014)

HIV Haplotype Inference Using a Propagating Dirichlet Process Mixture Model. - Sandhya Prabhakaran; Mélanie Rey; Osvaldo Zagordi; Niko Beerenwinkel; Volker Roth 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2014)

Copula Archetypal Analysis. - Dinu Kaufmann; Sebastian Keller 001; Volker Roth 001 (GCPR, 2015)

Probabilistic clustering of time-evolving distance data. - Julia E. Vogt; Marius Kloft; Stefan Stark; Sudhir Raman; Sandhya Prabhakaran; Volker Roth 001; Gunnar Rätsch (Mach. Learn., 2015)

Bayesian Markov Blanket Estimation. - Dinu Kaufmann; Sonali Parbhoo; Aleksander Wieczorek; Sebastian Keller 001; David Adametz; Volker Roth 001 (AISTATS, 2016)

Copula Eigenfaces - Semiparametric Principal Component Analysis for Facial Appearance Modeling. - Bernhard Egger 001; Dinu Kaufmann; Sandro Schönborn; Volker Roth 001; Thomas Vetter (VISIGRAPP (1: GRAPP), 2016)

Copula Eigenfaces with Attributes: Semiparametric Principal Component Analysis for a Combined Color, Shape and Attribute Model. - Bernhard Egger 001; Dinu Kaufmann; Sandro Schönborn; Volker Roth 001; Thomas Vetter (VISIGRAPP (Revised Selected Papers), 2016)

Combining Kernel and Model Based Learning for HIV Therapy Selection. - Sonali Parbhoo; Jasmina Bogojeska; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (CRI, 2017)

Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. - Mike Wu; Michael C. Hughes; Sonali Parbhoo; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2018)

Invexity Preserving Transformations for Projection Free Optimization with Sparsity Inducing Non-convex Constraints. - Sebastian Mathias Keller; Damian Murezzan; Volker Roth 001 (GCPR, 2018)

Learning Sparse Latent Representations with the Deep Copula Information Bottleneck. - Aleksander Wieczorek; Mario Wieser; Damian Murezzan; Volker Roth 001 (ICLR (Poster), 2018)

Causal Deep Information Bottleneck. - Sonali Parbhoo; Mario Wieser; Volker Roth 001 (CoRR, 2018)

Informed MCMC with Bayesian Neural Networks for Facial Image Analysis. - Adam Kortylewski; Mario Wieser; Andreas Morel-Forster; Aleksander Wieczorek; Sonali Parbhoo; Volker Roth 001; Thomas Vetter (CoRR, 2018)

Estimating Causal Effects With Partial Covariates For Clinical Interpretability. - Sonali Parbhoo; Mario Wieser; Volker Roth 001 (CoRR, 2018)

Computational EEG in Personalized Medicine: A study in Parkinson's Disease. - Sebastian Mathias Keller; Maxim Samarin; Antonia Meyer; Vitalii Kosak; Ute Gschwandtner; Peter Fuhr; Volker Roth 001 (CoRR, 2018)

Greedy Structure Learning of Hierarchical Compositional Models. - Adam Kortylewski; Aleksander Wieczorek; Mario Wieser; Clemens Blumer; Sonali Parbhoo; Andreas Morel-Forster; Volker Roth 001; Thomas Vetter (CVPR, 2019)

Deep Archetypal Analysis. - Sebastian Mathias Keller; Maxim Samarin; Mario Wieser; Volker Roth 001 (GCPR, 2019)

Tensor B-Spline Numerical Methods for PDEs: a High-Performance Alternative to FEM. - Dmytro Shulga; Oleksii Morozov; Volker Roth 001; Felix Friedrich; Patrick R. Hunziker (CoRR, 2019)

Regional Tree Regularization for Interpretability in Black Box Models. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (CoRR, 2019)

Information Theoretic Causal Effect Quantification. - Aleksander Wieczorek; Volker Roth 001 (Entropy, 2019)

Regional Tree Regularization for Interpretability in Deep Neural Networks. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2020)

Transfer Learning from Well-Curated to Less-Resourced Populations with HIV. - Sonali Parbhoo; Mario Wieser; Volker Roth 001; Finale Doshi-Velez (MLHC, 2020)

Inverse Learning of Symmetries. - Mario Wieser; Sonali Parbhoo; Aleksander Wieczorek; Volker Roth 001 (NeurIPS, 2020)

Inverse Learning of Symmetry Transformations. - Mario Wieser; Sonali Parbhoo; Aleksander Wieczorek; Volker Roth 001 (CoRR, 2020)

On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures. - Maxim Samarin; Volker Roth 001; David Belius (CoRR, 2020)

3DMolNet: A Generative Network for Molecular Structures. - Vitali Nesterov; Mario Wieser; Volker Roth 001 (CoRR, 2020)

Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates. - Sonali Parbhoo; Mario Wieser; Aleksander Wieczorek; Volker Roth 001 (Entropy, 2020)

On the Difference between the Information Bottleneck and the Deep Information Bottleneck. - Aleksander Wieczorek; Volker Roth 001 (Entropy, 2020)

Identifying Soil Erosion Processes in Alpine Grasslands on Aerial Imagery with a U-Net Convolutional Neural Network. - Maxim Samarin; Lauren Zweifel; Volker Roth 001; Christine Alewell (Remote. Sens., 2020)

Learning Conditional Invariance Through Cycle Consistency. - Maxim Samarin; Vitali Nesterov; Mario Wieser; Aleksander Wieczorek; Sonali Parbhoo; Volker Roth 001 (GCPR, 2021)

Learning Extremal Representations with Deep Archetypal Analysis. - Sebastian Mathias Keller; Maxim Samarin; Fabricio Arend Torres; Mario Wieser; Volker Roth 001 (Int. J. Comput. Vis., 2021)

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Volker Roth 001; Finale Doshi-Velez (J. Artif. Intell. Res., 2021)

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study. - Maxim Samarin; Volker Roth 001; David Belius (UAI, 2022)

Learning Invariances with Generalised Input-Convex Neural Networks. - Vitali Nesterov; Fabricio Arend Torres; Monika Nagy-Huber; Maxim Samarin; Volker Roth 001 (CoRR, 2022)

Truly Mesh-free Physics-Informed Neural Networks. - Fabricio Arend Torres; Marcello Massimo Negri; Monika Nagy-Huber; Maxim Samarin; Volker Roth 001 (CoRR, 2022)

Conditional Matrix Flows for Gaussian Graphical Models. - Marcello Massimo Negri; Fabricio Arend Torres; Volker Roth 001 (NeurIPS, 2023)

Lagrangian Flow Networks for Conservation Laws. - Fabricio Arend Torres; Marcello Massimo Negri; Marco Inversi; Jonathan Aellen; Volker Roth 001 (ICLR, 2024)

Injective Flows for parametric hypersurfaces. - Marcello Massimo Negri; Jonathan Aellen; Volker Roth 001 (CoRR, 2024)

Physics-informed boundary integral networks (PIBI-Nets): A data-driven approach for solving partial differential equations. - Monika Nagy-Huber; Volker Roth 001 (J. Comput. Sci., 2024)

Injective flows for star-like manifolds. - Marcello Massimo Negri; Jonathan Aellen; Volker Roth 001 (ICLR, 2025)

NIMO: a Nonlinear Interpretable MOdel. - Shijian Xu; Marcello Massimo Negri; Volker Roth 001 (CoRR, 2025)