UNIverse - Public Research Portal
Profile Photo

Prof. Dr. Volker Roth

Department of Mathematics and Computer Sciences
Profiles & Affiliations

Publications

144 found
Show per page

Arend Torres, Fabricio, Negri,Marcello Massimo, Inversi, Marco, Aellen, Jonathan, & Roth, Volker. (2024, May 7). Lagrangian Flow Networks for Conservation Laws. The Twelfth International Conference on Learning Representations. https://openreview.net/forum?id=Nshk5YpdWE

URLs
URLs

Hauke, Daniel J., Wobmann, Michelle, Andreou, Christina, Mackintosh, Amatya J., DE BOCK, Renate, Karvelis, Povilas, Adams, Rick A., Sterzer, Philipp, Borgwardt, Stefan, Roth, Volker, & Diaconescu, Andreea O. (2024). Altered Perception of Environmental Volatility During Social Learning in Emerging Psychosis. Computational Psychiatry, 8, 1–22. https://doi.org/10.5334/cpsy.95

URLs
URLs

Nagy-Huber, Monika, & Roth, Volker. (2024). Physics-informed boundary integral networks (PIBI-Nets): A data-driven approach for solving partial differential equations. Journal of Computational Science, 81. https://doi.org/10.1016/j.jocs.2024.102355

URLs
URLs

Schwendinger, Fabian, Biehler, Ann-Kathrin, Nagy-Huber, Monika, Knaier, Raphael, Roth, Volker, Dumitrescu, Daniel, Meyer, F. Joachim, Hager, Alfred, & Schmidt-Trucksäss, Arno. (2024). Using Machine Learning–Based Algorithms to Identify and Quantify Exercise Limitations in Clinical Practice: Are We There Yet? Medicine and Science in Sports and Exercise, 56, 159–169. https://doi.org/10.1249/mss.0000000000003293

URLs
URLs

Torres, Fabricio Arend, Negri, Marcello M., Inversi, Marco, Aellen, Jonathan, & Roth, Volker. (2024, January 1). LAGRANGIAN FLOW NETWORKS FOR CONSERVATION LAWS.

Gschwandtner, Ute, Bogaarts, Guy, Roth, Volker, & Fuhr, Peter. (2023). Prediction of cognitive decline in Parkinson’s disease (PD) patients with electroencephalography (EEG) connectivity characterized by time-between-phase-crossing (TBPC) [Journal-article]. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-32345-6

Gschwandtner, Ute, Bogaarts, Guy, Roth, Volker, & Fuhr, Peter. (2023). Prediction of cognitive decline in Parkinson’s disease (PD) patients with electroencephalography (EEG) connectivity characterized by time-between-phase-crossing (TBPC) [Journal-article]. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-32345-6

Hauke, D. J., Wobmann, M., Andreou, C., Mackintosh, A., de Bock, R., Karvelis, P., Adams, R. A., Sterzer, P., Borgwardt, S., Roth, V., & Diaconescu, A. O. (2023, February 6). Aberrant perception of environmental volatility during social learning in emerging psychosis [Posted-content]. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.02.02.23285371

URLs
URLs

Bedford, Peter, Hauke, Daniel J., Wang, Zheng, Roth, Volker, Nagy-Huber, Monika, Holze, Friederike, Ley, Laura, Vizeli, Patrick, Liechti, Matthias E., Borgwardt, Stefan, Müller, Felix, & Diaconescu, Andreea O. (2023). The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity. Neuropsychopharmacology, 48, 1175–1183. https://doi.org/10.1038/s41386-023-01574-8

URLs
URLs

Gschwandtner, Ute, Bogaarts, Guy, Roth, Volker, & Fuhr, Peter. (2023). Prediction of cognitive decline in Parkinson’s disease (PD) patients with electroencephalography (EEG) connectivity characterized by time-between-phase-crossing (TBPC). Scientific Reports, 13. https://doi.org/10.1038/s41598-023-32345-6

URLs
URLs

Hauke, Daniel J., Charlton, Colleen E., Schmidt, André, Griffiths, John D., Woods, Scott W., Ford, Judith M., Srihari, Vinod H., Roth, Volker, Diaconescu, Andreea O., & Mathalon, Daniel H. (2023). Aberrant Hierarchical Prediction Errors Are Associated With Transition to Psychosis: A Computational Single-Trial Analysis of the Mismatch Negativity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8, 1176–1185. https://doi.org/10.1016/j.bpsc.2023.07.011

URLs
URLs

Negri, Marcello Massimo, Arend Torres, Fabricio, & Roth, Volker. (2023). Conditional Matrix Flows for Gaussian Graphical Models. Advances in Neural Information Processing Systems, 36, 25095–25111. https://proceedings.neurips.cc/paper_files/paper/2023/file/4eef8829319316d0b552328715c836c3-Paper-Conference.pdf

URLs
URLs

Steppan, Martin, Zimmermann, Ronan, Fürer, Lukas, Southward, Matthew, Koenig, Julian, Kaess, Michael, Kleinbub, Johann Roland, Roth, Volker, & Schmeck, Klaus. (2023). Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study. Psychopathology, null. https://doi.org/10.1159/000534811

URLs
URLs

Hauke, D. J., Charlton, C. E., Schmidt, A., Griffiths, J., Woods, S. W., Ford, J. M., Srihari, V. H., Roth, V., Diaconescu, A. O., & Mathalon, D. H. (2022). Aberrant hierarchical prediction errors are associated with transition to psychosis: A computational single-trial analysis of the mismatch negativity [Posted-content]. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.12.20.22283712

URLs
URLs

Bedford, P., Hauke, D. J., Wang, Z., Roth, V., Nagy-Huber, M., Holze, F., Ley, L., Vizeli, P., Liechti, M. E., Borgwardt, S., Müller, F., & Diaconescu, A. O. (2022). The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity [Posted-content]. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.11.01.514687

URLs
URLs

Arend Torres, Fabricio, Negri, Marcello Massimo, Nagy-Huber, Monika, Samarin, Maxim, & Roth, Volker. (2022). Mesh-free eulerian physics-informed neural networks. https://doi.org/10.48550/arxiv.2206.01545

URLs
URLs

Hauke D.J., Roth V., Karvelis P., Adams R.A., Moritz S., Borgwardt S., Diaconescu A.O., & Andreou C. (2022). Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training. Schizophrenia Bulletin, 48, 826–838. https://doi.org/10.1093/schbul/sbac029

URLs
URLs

Hauke, D J, Roth, V, Karvelis, P, Adams, R A, Moritz, S, Borgwardt, S, Diaconescu, A O, & Andreou, C. (2022). Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training. Schizophrenia Bulletin, 48(4), 826–838. https://doi.org/10.1093/schbul/sbac029

Maxim Samarin, Volker Roth, & David Belius. (2022, January 1). Feature Learning and Random Features in Standard Finite-Width Convolutional Neural Networks: An Empirical Study. Uai. https://openreview.net/forum?id=ScIEZdIiqe5

URLs
URLs

Nesterov, Vitali, Torres, Fabricio Arend, Nagy-Huber, Monika, Samarin, Maxim, & Roth, Volker. (2022). Learning Invariances with Generalised Input-Convex Neural Networks. https://doi.org/10.48550/arxiv.2204.07009

URLs
URLs

Gschwandtner, Ute, Bogaarts, Guy, Chaturvedi, Menorca, Hatz, Florian, Meyer, Antonia, Fuhr, Peter, & Roth, Volker. (2021). Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain’s Functional Organization. Frontiers in Neuroscience, 15. https://doi.org/10.3389/fnins.2021.683633

URLs
URLs

Gschwandtner, Ute, Bogaarts, Guy, Chaturvedi, Menorca, Hatz, Florian, Meyer, Antonia, Fuhr, Peter, & Roth, Volker. (2021). Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain’s Functional Organization. Frontiers in Neuroscience, 15, 683633. https://doi.org/10.3389/fnins.2021.683633

Keller, Sebastian Mathias, Samarin, Maxim, Arend Torres, Fabricio, Wieser, Mario, & Roth, Volker. (2021). Learning Extremal Representations with Deep Archetypal Analysis. International Journal of Computer Vision, 129(4), 805–820. https://doi.org/10.1007/s11263-020-01390-3

URLs
URLs

Samarin, Maxim, Nesterov, Vitali, Wieser, Mario, Wieczorek, Aleksander, Parbhoo, Sonali, & Roth, Volker. (2021). Learning Conditional Invariance Through Cycle Consistency. 13024 LNCS, 376–391. https://doi.org/10.1007/978-3-030-92659-5_24

URLs
URLs

Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Roth, Volker, & Doshi-Velez, Finale. (2021). Optimizing for interpretability in deep neural networks with tree regularization. Journal of Artificial Intelligence Research, 72. https://doi.org/10.1613/jair.1.12558

URLs
URLs

Zimmermann, Ronan, Fürer, Lukas, Schenk, Nathalie, Koenig, Julian, Roth, Volker, Schlüter-Müller, Susanne, Kaess, Michael, & Schmeck, Klaus. (2021). Silence in the psychotherapy of adolescents with borderline personality pathology. Personality Disorders, 12(2), 160–170. https://doi.org/10.1037/per0000402

URLs
URLs

Keller, S. M., Gschwandtner, U., Meyer, A., Chaturvedi, M., Fuhr, P., & Roth, V. (2020). FV22 Reduced Tsallis Entropy of EEG in Patients with Parkinsons Disease – A Predictive Marker for Cognitive Decline [Journal-article]. Clinical Neurophysiology, 131(4), e233. https://doi.org/10.1016/j.clinph.2019.12.112

URLs
URLs

Samarin, M., Nagy-Huber, M., Zweifel, L., Meusburger, K., Alewell, C., & Roth, V. (2020). Visual Understanding in Semantic Segmentation of Soil Erosion Sites in Swiss Alpine Grasslands [Posted-content]. Copernicus GmbH. https://doi.org/10.5194/egusphere-egu2020-17346

URLs
URLs

Zweifel, L., Samarin, M., Meusburger, K., Roth, V., & Alewell, C. (2020). Identification of Soil Erosion in Alpine Grasslands on High-Resolution Aerial Images: Switching from Object-based Image Analysis to Deep Learning? [Posted-content]. Copernicus GmbH. https://doi.org/10.5194/egusphere-egu2020-2328

URLs
URLs

Keller, Sebastian M., Gschwandtner, Ute, Meyer, Antonia, Chaturvedi, Menorca, Roth, Volker, & Fuhr, Peter. (2020). Cognitive decline in Parkinson’s disease is associated with reduced complexity of EEG at baseline. Brain Communications, 2(2), fcaa207. https://doi.org/10.1093/braincomms/fcaa207

URLs
URLs

Kozak, Vitalii V., Chaturvedi, Menorca, Gschwandtner, Ute, Hatz, Florian, Meyer, Antonia, Roth, Volker, & Fuhr, Peter. (2020). EEG Slowing and Axial Motor Impairment Are Independent Predictors of Cognitive Worsening in a Three-Year Cohort of Patients With Parkinson’s Disease. Frontiers in Aging Neuroscience, 12, 171. https://doi.org/10.3389/fnagi.2020.00171

URLs
URLs

Nesterov, Vitali, Wieser, Mario, & Roth, Volker. (2020). 3DMolNet: A Generative Network for Molecular Structures. In Arxiv. Cornell University. https://doi.org/10.48550/arxiv.2010.06477

URLs
URLs

Parbhoo, Sonali, Wieser, Mario, Roth, Volker, & Doshi-Velez, Finale. (2020). Transfer Learning from Well-Curated to Less-Resourced Populations with HIV. In Doshi-Velez, F.; Fackler, J.; Jung, K.; Kale, D.; Ranganath, R.; Wallace, B.; Wiens, J. (Ed.), Proceedings of Machine Learning Research (Vol. 126). PMLR.

URLs
URLs

Parbhoo, Sonali, Wieser, Mario, Wieczorek, Aleksander, & Roth, Volker. (2020). Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates. Entropy, 22(4), 389. https://doi.org/10.3390/e22040389

URLs
URLs

Samarin, Maxim, Zweifel, Lauren, Roth, Volker, & Alewell, Christine. (2020). Identifying Soil Erosion Processes in Alpine Grasslands on Aerial Imagery with a U-Net Convolutional Neural Network. Remote Sensing, 12(24), 4149. https://doi.org/10.3390/rs12244149

URLs
URLs

Thorball, Christian W., Borghesi, Alessandro, Bachmann, Nadine, Von Siebenthal, Chantal, Vongrad, Valentina, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Roth, Volker, Kok, Yik Lim, Parbhoo, Sonali, Wieser, Mario, Böni, Jürg, Perreau, Matthieu, Klimkait, Thomas, Yerly, Sabine, Battegay, Manuel, Rauch, Andri, et al. (2020). Host Genomics of the HIV-1 Reservoir Size and Its Decay Rate During Suppressive Antiretroviral Treatment. Journal of Acquired Immune Deficiency Syndromes, 85(4), 517–524. https://doi.org/10.1097/qai.0000000000002473

URLs
URLs

Wan, Chenjie, Bachmann, Nadine, Mitov, Venelin, Blanquart, François, Céspedes, Susana Posada, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Fellay, Jacques, Roth, Volker, Böni, Jürg, Perreau, Matthieu, Klimkait, Thomas, Yerly, Sabine, Battegay, Manuel, Walti, Laura, Calmy, Alexandra, Vernazza, Pietro, et al. (2020). Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART. Nature Communications, 11(1), 5542. https://doi.org/10.1038/s41467-020-19198-7

URLs
URLs

Wieczorek, Aleksander, & Roth, Volker. (2020). On the Difference between the Information Bottleneck and the Deep Information Bottleneck. Entropy, 22(2), 131. https://doi.org/10.3390/e22020131

URLs
URLs

Wieser, Mario, Parbhoo, Sonali, Wieczorek, Aleksander, & Roth, Volker. (2020). Inverse Learning of Symmetries (Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M. F.; Lin, H., Ed.). Curran Associates, Inc.

URLs
URLs

Wieser, Mario, Parbhoo, Sonali, Wieczorek, Aleksander, & Roth, Volker. (2020). Inverse learning of symmetries. 2020-December.

Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Kindle, Ryan, Celi, Leo A., Zazzi, Maurizio, Roth, Volker, & Doshi-Velez, Finale. (2020). Regional Tree Regularization for Interpretability in Deep Neural Networks. Proceedings of the ... AAAI Conference on Artificial Intelligence, 34. https://doi.org/10.1609/aaai.v34i04.6112

URLs
URLs

Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Kindle, Ryan, Celi, Leo, Zazzi, Maurizio, Roth, Volker, & Doshi-Velez, Finale. (2020). Regional tree regularization for interpretability in deep neural networks. null, 6413–6421.

Thorball, C. W., Borghesi, A., Bachmann, N., von Siebenthal, C., Vongrad, V., Turk, T., Neumann, K., Beerenwinkel, N., Bogojeska, J., Roth, V., Kok, Y. L., Parbhoo, S., Wieser, M., Böni, J., Perreau, M., Klimkait, T., Yerly, S., Battegay, M., Rauch, A., et al. (2019, December 6). Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment [Posted-content]. Cold Spring Harbor Laboratory. https://doi.org/10.1101/19013763

URLs
URLs

Bachmann, Nadine, von Siebenthal, Chantal, Vongrad, Valentina, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Fellay, Jaques, Roth, Volker, Kok, Yik Lim, Thorball, Christian W., Borghesi, Alessandro, Parbhoo, Sonali, Wieser, Mario, Böni, Jürg, Perreau, Matthieu, Klimkait, Thomas, Yerly, Sabine, Battegay, Manuel, et al. (2019). Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-10884-9

URLs
URLs

Chaturvedi, M., Yilmaz, R., Gschwandtner, U., Greulich, K., Reimold, M., Fuhr, P., Roth, V., Timmers, M., Streffer, J., Berg, D., & Liepelt-Scarfone, I. (2019). FV 4 Electroencephalographic Activity as a potential prodromal marker for Parkinson’s disease [Journal-article]. Clinical Neurophysiology, 130(8), e122–e123. https://doi.org/10.1016/j.clinph.2019.04.614

URLs
URLs

Chaturvedi, Menorca, Bogaarts, Jan Guy, Kozak Cozac, Vitalii V., Hatz, Florian, Gschwandtner, Ute, Meyer, Antonia, Fuhr, Peter, & Roth, Volker. (2019). Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson’s disease. Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology, 130(10), 1937–1944. https://doi.org/10.1016/j.clinph.2019.07.017

URLs
URLs

Keller, Sebastian Mathias, Murezzan, Damian, & Roth, Volker. (2019). Invexity Preserving Transformations for Projection Free Optimization with Sparsity Inducing Non-convex Constraints. 11269 LNCS, 682–697. https://doi.org/10.1007/978-3-030-12939-2_47

URLs
URLs

Keller, Sebastian Mathias, Samarin, Maxim, Wieser, Mario, & Roth, Volker. (2019). Deep Archetypal Analysis. In Fink, Gernot A.; Frintrop, Simone; Jiang, Xiaoyi (Ed.), Lecture Notes in Computer Science. Springer International Publishing. https://doi.org/10.1007/978-3-030-33676-9_12

URLs
URLs

Kortylewski, Adam, Wieczorek, Aleksander, Wieser, Mario, Blumer, Clemens, Parbhoo, Sonali, Morel-Forster, Andreas, Roth, Volker, & Vetter, Thomas. (2019, January 1). Greedy Structure Learning of Hierarchical Compositional Models. https://doi.org/10.1109/cvpr.2019.01188

URLs
URLs

Wieczorek, Aleksander, & Roth, Volker. (2019). Information Theoretic Causal Effect Quantification. Entropy, 21(10), 975. https://doi.org/10.3390/e21100975

URLs
URLs

Bogaarts, J. G., Chaturvedi, M., Cozac, V., Gschwandtner, U., Hardmeier, M., Hatz, F., Meyer, A., Fuhr, P., & Roth, V. (2018). P30. A novel application of the Phase-lag-Index in functional connectivity research [Journal-article]. Clinical Neurophysiology, 129(8), e79. https://doi.org/10.1016/j.clinph.2018.04.671

URLs
URLs

Chaturvedi, M., Bogaarts, J. G., Hatz, F., Cozac, V., Meyer, A., Gschwandtner, U., Liepelt-Scarfone, I., Babiloni, C., Fuhr, P., & Roth, V. (2018). P78. Can Phase Lag Index (PLI) be beneficial in distinguishing Parkinsons disease Dementia (PDD) patients from Parkinsons disease (PD) patients? [Journal-article]. Clinical Neurophysiology, 129(8), e99. https://doi.org/10.1016/j.clinph.2018.04.710

URLs
URLs

Cozac, V., Bogaarts, J. G., Chaturvedi, M., Gschwandtner, U., Hatz, F., Meyer, A., Roth, V., & Fuhr, P. (2018). P76. Axial impairment and EEG slowing are independent predictors of cognitive outcome in a three-year cohort of PD patients [Journal-article]. Clinical Neurophysiology, 129(8), e98. https://doi.org/10.1016/j.clinph.2018.04.708

URLs
URLs

Chaturvedi, M., Bogaarts, J., Hatz, F., Gschwandtner, U., Cozac, V., Meyer, A., Liepelt, I., Babiloni, C., Fuhr, P., & Roth, V. (2018). F67. Distinguishing Parkinson’s Disease Dementia (PDD) patients from Parkinson’s Disease (PD) patients using EEG frequency and connectivity measures [Journal-article]. Clinical Neurophysiology, 129, e92. https://doi.org/10.1016/j.clinph.2018.04.230

URLs
URLs

Parbhoo, Sonali, Gottesman, Omer, Ross, Andrew Slavin, Komorowski, Matthieu, Faisal, Aldo, Bon, Isabella, Roth, Volker, & Doshi-Velez, Finale. (2018). Improving counterfactual reasoning with kernelised dynamic mixing models. PloS One, 13(11), e0205839. https://doi.org/10.1371/journal.pone.0205839

URLs
URLs

Wieczorek, Aleksander, Wieser, Mario, Murezzan, Damian, & Roth, Volker. (2018). Learning sparse latent representations with the deep copula information bottleneck. null.

Wieser, Mario, Wieczorek, Aleksander, Murezzan, Damian, & Roth, Volker. (2018, January 1). Learning Sparse Latent Representations with the Deep Copula Information Bottleneck. https://openreview.net/forum?id=Hk0wHx-RW

URLs
URLs

Wu, Mike, Hughes, Michael C., Parbhoo, Sonali, Zazzi, Maurizio, Roth, Volker, & Doshi-Velez, Finale. (2018, January 1). Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16285

URLs
URLs

Wu, Mike, Hughes, Michael C., Parbhoo, Sonali, Zazzi, Maurizio, Roth, Volker, & Doshi-Velez, Finale. (2018). Beyond sparsity: Tree regularization of deep models for interpretability. null, 1670–1678.

Chaturvedi, M., Hatz, F., Gschwandtner, U., Meyer, A., Cozac, V. V., Bogaarts, J. G., Roth, V., & Fuhr, P. (2017). P 129 Quantitative EEG and neuropsychological tests to differentiate between Parkinson’s disease patients and healthy controls with Random Forest algorithm [Journal-article]. Clinical Neurophysiology, 128(10), e391–e392. https://doi.org/10.1016/j.clinph.2017.06.202

URLs
URLs

Chaturvedi, M., Hatz, F., Gschwandtner, U., Bogaarts, J. G., Meyer, A., Fuhr, P., & Roth., V. (2017). Quantitative EEG (QEEG) Measures Differentiate Parkinson`s Disease Patients from Healthy Controls. Frontiers in Aging Neuroscience, 9(3), 3. https://doi.org/10.3389/fnagi.2017.00003

URLs
URLs

Egger, Bernhard, Kaufmann, Dinu, Schönborn, Sandro, Roth, Volker, & Vetter, Thomas. (2017). Copula Eigenfaces with Attributes: Semiparametric Principal Component Analysis for a Combined Color, Shape and Attribute Model. Communications in Computer and Information Science, 693, 95–112. https://doi.org/10.1007/978-3-319-64870-5_5

URLs
URLs

Parbhoo, Sonali, Bogojeska, Jasmina, Zazzi, Maurizio, Roth, Volker, & Doshi-Velez, Finale. (2017). Combining Kernel and Model Based Learning for HIV Therapy Selection. Amia Summits on Translational Science Proceedings, 2017, 239–248. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543338/

URLs
URLs

Roth, Volker, & Vetter, Thomas. (2017). Preface. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10496 LNCS.

Chaturvedi, M., Hatz, F., Meyer, A., Cozac, V., Gschwandtner, U., Roth, V., & Fuhr, P. (2016). Can Quantitative EEG (QEEG) differentiate patients with Parkinson’s disease (PD) from healthy controls? [Journal-article]. Parkinsonism & Related Disorders, 22, e163. https://doi.org/10.1016/j.parkreldis.2015.10.388

URLs
URLs

Dazert, E., Colombi, M., Boldanova, T., Moes, S., Adametz, D., Quagliata, L., Roth, V., Terracciano, L., Heim, M. H., Jenoe, P., & Hall, M. N. (2016). Quantitative proteomics and phosphoproteomics on serial tumor biopsies from a sorafenib-treated HCC patient. Proceedings of the National Academy of Sciences of the United States of America, 113(5), 1381–1386. https://doi.org/10.1073/pnas.1523434113

URLs
URLs

Egger, Bernhard, Kaufmann, Dinu, Schönborn, Sandro, Roth, Volker, & Vetter, Thomas. (2016, January 1). Copula Eigenfaces - Semiparametric Principal Component Analysis for Facial Appearance Modeling. https://doi.org/10.5220/0005718800480056

URLs
URLs

Kaufmann, Dinu, Parbhoo, Sonali, Wieczorek, Aleksander, Keller, Sebastian, Adametz, David, & Roth, Volker. (2016). Bayesian Markov Blanket Estimation. Proceedings of Machine Learning Research, 51. http://jmlr.org/proceedings/papers/v51/kaufmann16.html

URLs
URLs

Kaufmann, Dinu, Parbhoo, Sonali, Wieczorek, Aleksander, Keller, Sebastian, Adametz, David, & Roth, Volker. (2016). Bayesian markov blanket estimation. null, 333–341.

Makowska, Zuzanna, Boldanova, Tujana, Adametz, David, Quagliata, Luca, Quagliata, Luca, Vogt, Julia E., Dill, Michael T., Matter, Mathias S., Roth, Volker, Terracciano, Luigi, & Heim, Markus H. (2016). Gene expression analysis of biopsy samples reveals critical limitations of transcriptome-based molecular classifications of hepatocellular carcinoma. The Journal of Pathology : Clinical Research, 2(2), 80–92. https://doi.org/10.1002/cjp2.37

URLs
URLs

Makowska, Z., Boldanova, T., Adametz, D., Quagliata, L., Vogt, J. E., Dill, M. T., Matter, M. S., Roth, V., Terracciano, L., & Heim, M. H. (2015). P0309 : Gene expression profiling of hepatocellular carcinoma biopsies reveals three molecular classes with distinct clinical and biological properties [Journal-article]. Journal of Hepatology, 62, S424–S425. https://doi.org/10.1016/s0168-8278(15)30524-9

URLs
URLs

Adametz, David, & Roth, Volker. (2015). Distance-based network recovery under feature correlation. 9370, 209–210.

Alewell, Christine, Meusburger, Katrin, Kandl, Daniela, Fetai, Ilir, Roth, Volker, Rugolo, Valentino, Schuldt, Heiko, & Vetter, Thomas. (2015). COSA - AlpErosion: Monitoring the degradation of Alpine soils with COSA, a Citizens’ Observatory Smartphone App (Patent No. 36). 36, Article 36. Bulletin der Bodenkundlichen Gesellschaft der Schweiz.

URLs
URLs

Vogt, Julia E., Kloft, Marius, Stark, Stefan, Raman, Sudhir S., Prabhakaran, Sandhya, Roth, Volker, & Raetsch, Gunnar. (2015). Probabilistic clustering of time-evolving distance data. Machine Learning, 100(2-3), 635–654. https://doi.org/10.1007/s10994-015-5516-x

URLs
URLs

Kaufmann, Dinu, Keller, Sebastian, & Roth, Volker. (2015). Copula Archetypal Analysis. In Gall, Juergen; Gehler, Peter; Leibe, Bastian (ed.), Pattern Recognition (pp. 117–128). Springer. https://doi.org/10.1007/978-3-319-24947-6_10

URLs
URLs

Bousleiman, H., Ahmed, S., Hardmeier, M., Hatz, F., Schindler, C., Roth, V., Zimmermann, R., Gschwandtner, U., & Fuhr, P. (2014). Quantitative EEG (qEEG) as Marker for Mild Cognitive Impairment (MCI) in Patients with Parkinson’s Disease (PD) (P5.059) [Journal-article]. Neurology, 82(10_supplement). https://doi.org/10.1212/wnl.82.10_supplement.p5.059

URLs
URLs

Bousleiman, Habib, Zimmermann, Ronan, Ahmed, Shaheen, Hardmeier, Martin, Hatz, Florian, Schindler, Christian, Roth, Volker, Gschwandtner, Ute, & Fuhr, Peter. (2014). Power spectra for screening parkinsonian patients for mild cognitive impairment. Annals of Clinical and Translational Neurology, 1(11), 884–890. https://doi.org/10.1002/acn3.129

Dill, Michael T., Makowska, Zuzanna, Trincucci, Gaia, Gruber, Andreas J., Vogt, Julia E., Filipowicz, Magdalena, Calabrese, Diego, Krol, Ilona, Lau, Daryl T., Terracciano, Luigi, van Nimwegen, Erik, Roth, Volker, & Heim, Markus H. (2014). Pegylated IFN-α regulates hepatic gene expression through transient Jak/STAT activation. Journal of Clinical Investigation, 124(4), 1568–1581. https://doi.org/10.1172/jci70408

URLs
URLs

Dill, M.T., Makowska, Z., Trincucci, G., Gruber, A.J., Vogt, J.E., Filipowicz, M., Calabrese, D., Krol, I., Lau, D.T., Terracciano, L., van Nimwegen, E., Roth, V., & Heim, M.H. (2014). O47 PEGYLATED INTERFERON-ALPHA INDUCES SUSTAINED TRANSCRIPTIONAL RESPONSE IN LIVER INFILTRATING IMMUNE CELLS BUT NOT IN HEPATOCYTES IN THE LIVER OF PATIENTS WITH CHRONIC HEPATITIS C. Journal of Hepatology, 60, S1–S22. https://doi.org/10.1016/s0168-8278(14)60049-0

URLs
URLs

Giallonardo, Francesca Di, Töpfer, Armin, Rey, Melanie, Prabhakaran, Sandhya, Duport, Yannick, Leemann, Christine, Schmutz, Stefan, Campbell, Nottania K., Joos, Beda, Lecca, Maria Rita, Patrignani, Andrea, Däumer, Martin, Beisel, Christian, Rusert, Peter, Trkola, Alexandra, Günthard, Huldrych F., Roth, Volker, Beerenwinkel, Niko, & Metzner, Karin J. (2014). Full-length haplotype reconstruction to infer the structure of heterogeneous virus populations. Nucleic Acids Research, 42(14), e115. https://doi.org/10.1093/nar/gku537

URLs
URLs

Prabhakaran, Sandhya, Rey, Melanie, Zagordi, Osvaldo, Beerenwinkel, Niko, & Roth, Volker. (2014). HIV Haplotype Inference Using a Propagating Dirichlet Process Mixture Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), 182–191. https://doi.org/ea017b9f-ec09-4077-85ab-ded3af538c48

URLs
URLs

Prabhakaran, Sandhya, Rey, Melanie, Zagordi, Osvaldo, Beerenwinkel, Niko, & Roth, Volker. (2014). HIV haplotype inference using a propagating dirichlet process mixture model. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11, 182–191. https://doi.org/10.1109/tcbb.2013.145

URLs
URLs

Rey, Melani, Roth, Volker, & Fuchs, Thomas. (2014). Sparse meta-Gaussian information bottleneck (Jebara,Tony;Xing,Eric P., Ed.). Curran. http://jmlr.org/proceedings/papers/v32/rey14.pdf

URLs
URLs

Adametz, David, Rey, Melanie, & Roth, Volker. (2014). Information Bottleneck for Pathway-Centric Gene Expression Analysis. In Jiang, X; Hornegger, J; Koch, R (Ed.), Pattern recognition: 36th German Conference (p. S. 81–91). Springer International Publishing. https://doi.org/10.1007/978-3-319-11752-2_7

URLs
URLs

Adametz, David, & Roth, Volker. (2014). Distance-based network recovery under feature correlation. In Z. Ghahramani and M. Welling and C. Cortes and N.D. Lawrence and K.Q. Weinberger (Ed.), Advances in neural information processing systems (Vol. 27, p. S. 775–783). MIT-Press. http://papers.nips.cc/paper/5470-distance-based-network-recovery-under-feature-correlation.pdf

URLs
URLs

Prabhakaran, Sandhya, Adametz, David, Metzner, Karin J., Boehm, Alexander, & Roth, Volker. (2013). Recovering networks from distance data. Machine Learning, 92(2-3), 251–283. https://doi.org/10.1007/s10994-013-5370-7

URLs
URLs

Rey, Melanie Rey, & Roth, Volker. (2013). Meta-Gaussian information bottleneck (Bartlett,P; Pereira,F.C.N.;Burges,C.J.C.,Bottou,L.; Weinberger,K.Q.}, Ed.; Vol. 25). The MIT Press.

URLs
URLs

Roth, V., Fuchs, T. J., Vogt, J. E., Prabhakaran, S., & Buhmann, J. M. (2013). Structure Preserving Embedding of Dissimilarity Data (pp. 157–177). Springer London. https://doi.org/10.1007/978-1-4471-5628-4_7

URLs
URLs

Töpfer, Armin, Zagordi, Osvaldo, Prabhakaran, Sandhya, Roth, Volker, Halperin, Eran, & Beerenwinkel, Niko. (2013). Probabilistic inference of viral quasispecies subject to recombination. Journal of Computational Biology, 20(2), 113–123. https://doi.org/10.1089/cmb.2012.0232

URLs
URLs

Wigger, Leonore, Vogt, Julia E, & Roth, Volker. (2013). Malaria haplotype frequency estimation. Statistics in Medicine, 32(21), 3737–3751. https://doi.org/10.1002/sim.5792

URLs
URLs

Makowska, Z., Dill, M. T., Vogt, J. E., Filipowicz, M., Terraciano, L., Roth, V., & Heim, M. H. (2012). P139 Continuous exposure to PEG-IFN-Alpha only transiently activates JAK-stat signalling in human liver [Journal-article]. Cytokine, 59(3), 563–564. https://doi.org/10.1016/j.cyto.2012.06.231

URLs
URLs

Beerenwinkel, Niko, Günthard, Huldrych F, Roth, Volker, & Metzner, Karin J. (2012). Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data. Frontiers in Microbiology, 3(00329), 329. https://doi.org/10.3389/fmicb.2012.00329

URLs
URLs

Melanie, Rey, & Roth, Volker. (2012). Copula mixture model for eependency-seeking clustering. 8 S. http://icml.cc/2012/papers/486.pdf

URLs
URLs

Meyer, Stefanie, Fuchs, Thomas J., Bosserhoff, Anja K., Hofstädter, Ferdinand, Pauer, Armin, Roth, Volker, Buhmann, Joachim M., Moll, Ingrid, Anagnostou, Nikos, Brandner, Johanna M., Ikenberg, Kristian, Moch, Holger, Landthaler, Michael, Vogt, Thomas, & Wild, Peter J. (2012). A seven-marker signature and clinical outcome in malignant melanoma : a large-scale tissue-microarray study with two independent patient cohorts. PLoS ONE, 7(6). https://doi.org/10.1371/journal.pone.0038222

URLs
URLs

Prabhakaran, Sandhya, Metzner, Karin J., Boehm, Alexander, & Roth, Volker. (2012). Recovering Networks from Distance Data. Journal of Machine Learning Research, 25, 349–364.

URLs
URLs

Prabhakaran, Sandhya, Metzner, Karin J., Böhm, Alexander, & Roth, Volker. (2012). Recovering networks from distance data. 25, 349–364.

Prabhakaran, Sandhya, Raman, Sudhir, Vogt, Julia E., & Roth, Volker. (2012). Automatic model selection in archetype analysis. In Pinz, Axel; Pock, Thomas; Bischof, Horst; Leberl, Franz (Ed.), Lecture notes in computer science. Springer. https://doi.org/10.1007/978-3-642-32717-9_46

URLs
URLs

Raman, Sudhir, & Roth, Volker. (2012). Sparse point estimation for Bayesian regression via simulated annealing. In Pinz, Axel; Pock, Thomas; Bischof, Horst; Leberl, Franz (Ed.), Lecture Notes in Computer Science. Springer. https://doi.org/10.1007/978-3-642-32717-9_32

URLs
URLs

Rey, Mélanie, & Roth, Volker. (2012). Meta-Gaussian information bottleneck. 3, 1916–1924.

Rey, Mélanie, & Roth, Volker. (2012). Copula mixture model for dependency-seeking clustering. 1, 927–934.