V. Roth

发表

The generalized LASSO

Volker Roth, V. Roth, Volker Roth, 2004, IEEE Transactions on Neural Networks.

The Generalized LASSO: a wrapper approach to gene selection for microarray data

V. Roth, 2002 .

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization pdf

Mike Wu, Finale Doshi-Velez, Volker Roth, 2019, J. Artif. Intell. Res..

Kernel Fisher Discriminants for Outlier Detection

V. Roth, 2006 .

Improved functional prediction of proteins by learning kernel combinations in multilabel settings

Volker Roth, Bernd Fischer, V. Roth, 2007, BMC Bioinformatics.

Pattern Recognition Combining Feature- and Pixel-Based Classification Within a Real World Application

Volker Roth, Stefan Schröder, Volker Steinhage, 1999, DAGM-Symposium.

Estimating Causal Effects With Partial Covariates For Clinical Interpretability pdf

Volker Roth, Mario Wieser, Sonali Parbhoo, 2018, ArXiv.

Supervised Speaker Diarization Using Random Forests: A Tool for Psychotherapy Process Research

V. Roth, R. Zimmermann, Lukas Fürer, 2020, Frontiers in Psychology.

Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment

V. Roth, J. Fellay, K. Metzner, 2019 .

Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates

V. Roth, S. Parbhoo, Mario Wieser, 2018, 1807.02326.

Causal Compression

V. Roth, Aleksander Wieczorek, 2016, 1611.00261.

Learning Extremal Representations with Deep Archetypal Analysis pdf

Maxim Samarin, Volker Roth, Mario Wieser, 2020, International Journal of Computer Vision.

Deep Archetypal Analysis pdf

Volker Roth, Maxim Samarin, Mario Wieser, 2019, GCPR.

A Complete Analysis of the l_1, p Group-Lasso pdf

Volker Roth, Julia E. Vogt, V. Roth, 2012, ICML.

Outlier Detection with One-class Kernel Fisher Discriminants

Volker Roth, V. Roth, 2004, NIPS.

Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma

Joachim M. Buhmann, Volker Roth, Cheng Soon Ong, 2013, Similarity-Based Pattern Analysis and Recognition.

Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment.

V. Roth, J. Fellay, K. Metzner, 2020, Journal of acquired immune deficiency syndromes.

Deep Sequencing of a Genetically Heterogeneous Sample: Local Haplotype Reconstruction and Read Error Correction

Volker Roth, Niko Beerenwinkel, Lukas Geyrhofer, 2009, RECOMB.

Regional Tree Regularization for Interpretability in Deep Neural Networks

Mike Wu, Finale Doshi-Velez, Volker Roth, 2020, AAAI.

Regional Tree Regularization for Interpretability in Black Box Models pdf

Mike Wu, Finale Doshi-Velez, Volker Roth, 2019, ArXiv.

Kernel Fisher Discriminants for Outlier Detection

Volker Roth, V. Roth, 2006, Neural Computation.

A Hidden Markov Model for de Novo Peptide Sequencing

Joachim M. Buhmann, Volker Roth, Peter Widmayer, 2004, NIPS.

Structure Preserving Embedding of Dissimilarity Data

Joachim M. Buhmann, Volker Roth, Thomas J. Fuchs, 2013, Similarity-Based Pattern Analysis and Recognition.

Improving counterfactual reasoning with kernelised dynamic mixing models

Andrew Slavin Ross, Volker Roth, Finale Doshi-Velez, 2018, PloS one.

Infinite mixture-of-experts model for sparse survival regression with application to breast cancer

Joachim M. Buhmann, Volker Roth, Edgar Dahl, 2010, BMC Bioinformatics.

Sparse Bayesian Regression for Grouped Variables in Generalized Linear Models

Volker Roth, Sudhir Raman, V. Roth, 2009, DAGM-Symposium.

3DMolNet: A Generative Network for Molecular Structures pdf

Volker Roth, Vitali Nesterov, Mario Wieser, 2020, ArXiv.

Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART

V. Roth, A. Trkola, J. Fellay, 2020, Nature Communications.

On the information and representation of non-Euclidean pairwise data

Joachim M. Buhmann, Volker Roth, Klaus-Robert Müller, 2006, Pattern Recognit..

Clustering with the Connectivity Kernel

Joachim M. Buhmann, Volker Roth, Bernd Fischer, 2003, NIPS.

Going Metric: Denoising Pairwise Data

Joachim M. Buhmann, Volker Roth, Klaus-Robert Müller, 2002, NIPS.

Recovering networks from distance data

Volker Roth, Karin J. Metzner, Sandhya Prabhakaran, 2012, Machine Learning.

Pattern Recognition Combining De-noising and Linear Discriminant Analysis within a Real World Application

Armin B. Cremers, Volker Roth, Stefan Schröder, 1999, CAIP.

Tensor B-Spline Numerical Methods for PDEs: a High-Performance Alternative to FEM pdf

Volker Roth, Patrick R. Hunziker, Felix Friedrich, 2019, ArXiv.

Bayesian class discovery in microarray datasets

Volker Roth, Tilman Lange, V. Roth, 2004, IEEE Transactions on Biomedical Engineering.

A Resampling Approach to Cluster Validation

Joachim M. Buhmann, Volker Roth, Mikio L. Braun, 2002, COMPSTAT.

Bayesian Partitioning of Large-Scale Distance Data

David Adametz, Volker Roth, V. Roth, 2011, NIPS.

Nonnegative CCA for Audiovisual Source Separation

C. Sigg, B. Fischer, B. Ommer, 2007, 2007 IEEE Workshop on Machine Learning for Signal Processing.

Probabilistic clustering of time-evolving distance data

Julia E. Vogt, Stefan G. Stark, V. Roth, 2015, Machine-mediated learning.

The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data

Volker Roth, Thomas J. Fuchs, Julia E. Vogt, 2010, ICML.

Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates

Volker Roth, Mario Wieser, Sonali Parbhoo, 2020, Entropy.

Causal Deep Information Bottleneck pdf

Volker Roth, Mario Wieser, Sonali Parbhoo, 2018, ArXiv.

Informed MCMC with Bayesian Neural Networks for Facial Image Analysis pdf

Adam Kortylewski, Volker Roth, Andreas Morel-Forster, 2018, ArXiv.

Distance-Based Network Recovery under Feature Correlation

David Adametz, Volker Roth, V. Roth, 2014, NIPS.

On the Difference between the Information Bottleneck and the Deep Information Bottleneck

V. Roth, Aleksander Wieczorek, 2019, Entropy.

Feature Selection in Clustering Problems

Volker Roth, Tilman Lange, V. Roth, 2003, NIPS.

Probabilistic Discriminative Kernel Classifiers for Multi-class Problems

Volker Roth, V. Roth, 2001, DAGM-Symposium.

Sparse Point Estimation for Bayesian Regression via Simulated Annealing

Volker Roth, Sudhir Raman, V. Roth, 2012, DAGM/OAGM Symposium.

Regional Tree Regularization for Interpretability in Deep Neural Networks

V. Roth, L. Celi, S. Parbhoo, 2019, AAAI Conference on Artificial Intelligence.

Bayesian Markov Blanket Estimation pdf

David Adametz, Volker Roth, Dinu Kaufmann, 2015, AISTATS.

Copula Mixture Model for Dependency-seeking Clustering pdf

Volker Roth, Mélanie Rey, V. Roth, 2012, ICML.