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Arend Torres, Fabricio, Negri,Marcello Massimo, Inversi, Marco, Aellen, Jonathan, & The Twelfth International Conference on Learning Representations. https://openreview.net/forum?id=Nshk5YpdWE
. (2024, May 7). Lagrangian Flow Networks for Conservation Laws. Hauke, Daniel J., Wobmann, Michelle, Andreou, Christina, Mackintosh, Amatya J., DE BOCK, Renate, Karvelis, Povilas, Adams, Rick A., Sterzer, Philipp, Borgwardt, Stefan, Computational Psychiatry, 8, 1–22. https://doi.org/10.5334/cpsy.95
, & Diaconescu, Andreea O. (2024). Altered Perception of Environmental Volatility During Social Learning in Emerging Psychosis. Nagy-Huber, Monika, & Journal of Computational Science, 81. https://doi.org/10.1016/j.jocs.2024.102355
. (2024). Physics-informed boundary integral networks (PIBI-Nets): A data-driven approach for solving partial differential equations. Schwendinger, Fabian, Biehler, Ann-Kathrin, Nagy-Huber, Monika, Knaier, Raphael, Medicine and Science in Sports and Exercise, 56, 159–169. https://doi.org/10.1249/mss.0000000000003293
, 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? Torres, Fabricio Arend, Negri, Marcello M., Inversi, Marco, Aellen, Jonathan, & LAGRANGIAN FLOW NETWORKS FOR CONSERVATION LAWS.
. (2024, January 1). Gschwandtner, Ute, Bogaarts, Guy, Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-32345-6
, & 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]. Gschwandtner, Ute, Bogaarts, Guy, Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-32345-6
, & 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]. Bedford, Peter, Hauke, Daniel J., Wang, Zheng, Neuropsychopharmacology, 48, 1175–1183. https://doi.org/10.1038/s41386-023-01574-8
, 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. Gschwandtner, Ute, Bogaarts, Guy, Scientific Reports, 13. https://doi.org/10.1038/s41598-023-32345-6
, & Fuhr, Peter. (2023). Prediction of cognitive decline in Parkinson’s disease (PD) patients with electroencephalography (EEG) connectivity characterized by time-between-phase-crossing (TBPC). Hauke, Daniel J., Charlton, Colleen E., Schmidt, André, Griffiths, John D., Woods, Scott W., Ford, Judith M., Srihari, Vinod H., Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8, 1176–1185. https://doi.org/10.1016/j.bpsc.2023.07.011
, 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. Negri, Marcello Massimo, Arend Torres, Fabricio, & Advances in Neural Information Processing Systems, 36, 25095–25111. https://proceedings.neurips.cc/paper_files/paper/2023/file/4eef8829319316d0b552328715c836c3-Paper-Conference.pdf
. (2023). Conditional Matrix Flows for Gaussian Graphical Models. Steppan, Martin, Zimmermann, Ronan, Fürer, Lukas, Southward, Matthew, Koenig, Julian, Kaess, Michael, Kleinbub, Johann Roland, Psychopathology, null. https://doi.org/10.1159/000534811
, & Schmeck, Klaus. (2023). Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study. 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
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
Arend Torres, Fabricio, Negri, Marcello Massimo, Nagy-Huber, Monika, Samarin, Maxim, & Mesh-free eulerian physics-informed neural networks. https://doi.org/10.48550/arxiv.2206.01545
. (2022). Hauke D.J., Schizophrenia Bulletin, 48, 826–838. https://doi.org/10.1093/schbul/sbac029
, 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. Hauke, D J, Schizophrenia Bulletin, 48(4), 826–838. https://doi.org/10.1093/schbul/sbac029
, 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. Maxim Samarin, Uai. https://openreview.net/forum?id=ScIEZdIiqe5
, & David Belius. (2022, January 1). Feature Learning and Random Features in Standard Finite-Width Convolutional Neural Networks: An Empirical Study. Nesterov, Vitali, Torres, Fabricio Arend, Nagy-Huber, Monika, Samarin, Maxim, & Learning Invariances with Generalised Input-Convex Neural Networks. https://doi.org/10.48550/arxiv.2204.07009
. (2022). Gschwandtner, Ute, Bogaarts, Guy, Chaturvedi, Menorca, Hatz, Florian, Meyer, Antonia, Fuhr, Peter, & Frontiers in Neuroscience, 15, 683633. https://doi.org/10.3389/fnins.2021.683633
. (2021). Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain’s Functional Organization. Gschwandtner, Ute, Bogaarts, Guy, Chaturvedi, Menorca, Hatz, Florian, Meyer, Antonia, Fuhr, Peter, & Frontiers in Neuroscience, 15. https://doi.org/10.3389/fnins.2021.683633
. (2021). Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain’s Functional Organization. Keller, Sebastian Mathias, Samarin, Maxim, Arend Torres, Fabricio, Wieser, Mario, & International Journal of Computer Vision, 129(4), 805–820. https://doi.org/10.1007/s11263-020-01390-3
. (2021). Learning Extremal Representations with Deep Archetypal Analysis. Samarin, Maxim, Nesterov, Vitali, Wieser, Mario, Wieczorek, Aleksander, Parbhoo, Sonali, & Learning Conditional Invariance Through Cycle Consistency. 13024 LNCS, 376–391. https://doi.org/10.1007/978-3-030-92659-5_24
. (2021). Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Journal of Artificial Intelligence Research, 72. https://doi.org/10.1613/jair.1.12558
, & Doshi-Velez, Finale. (2021). Optimizing for interpretability in deep neural networks with tree regularization. Zimmermann, Ronan, Fürer, Lukas, Schenk, Nathalie, Koenig, Julian, Personality Disorders, 12(2), 160–170. https://doi.org/10.1037/per0000402
, Schlüter-Müller, Susanne, Kaess, Michael, & Schmeck, Klaus. (2021). Silence in the psychotherapy of adolescents with borderline personality pathology. Keller, S. M., Gschwandtner, U., Meyer, A., Chaturvedi, M., Fuhr, P., & Clinical Neurophysiology, 131(4), e233. https://doi.org/10.1016/j.clinph.2019.12.112
(2020). FV22 Reduced Tsallis Entropy of EEG in Patients with Parkinsons Disease – A Predictive Marker for Cognitive Decline [Journal-article]. 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
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
Keller, Sebastian M., Gschwandtner, Ute, Meyer, Antonia, Chaturvedi, Menorca, Brain Communications, 2(2), fcaa207. https://doi.org/10.1093/braincomms/fcaa207
, & Fuhr, Peter. (2020). Cognitive decline in Parkinson’s disease is associated with reduced complexity of EEG at baseline. Kozak, Vitalii V., Chaturvedi, Menorca, Gschwandtner, Ute, Hatz, Florian, Meyer, Antonia, Frontiers in Aging Neuroscience, 12, 171. https://doi.org/10.3389/fnagi.2020.00171
, & 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. Nesterov, Vitali, Wieser, Mario, & Arxiv. Cornell University. https://doi.org/10.48550/arxiv.2010.06477
. (2020). 3DMolNet: A Generative Network for Molecular Structures. In Parbhoo, Sonali, Wieser, Mario, Proceedings of Machine Learning Research (Vol. 126). PMLR.
, & 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.), Parbhoo, Sonali, Wieser, Mario, Wieczorek, Aleksander, & Entropy, 22(4), 389. https://doi.org/10.3390/e22040389
. (2020). Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates. Samarin, Maxim, Zweifel, Lauren, Remote Sensing, 12(24), 4149. https://doi.org/10.3390/rs12244149
, & Alewell, Christine. (2020). Identifying Soil Erosion Processes in Alpine Grasslands on Aerial Imagery with a U-Net Convolutional Neural Network. Thorball, Christian W., Borghesi, Alessandro, Bachmann, Nadine, Von Siebenthal, Chantal, Vongrad, Valentina, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Journal of Acquired Immune Deficiency Syndromes, 85(4), 517–524. https://doi.org/10.1097/qai.0000000000002473
, 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. Wan, Chenjie, Bachmann, Nadine, Mitov, Venelin, Blanquart, François, Céspedes, Susana Posada, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Fellay, Jacques, Nature Communications, 11(1), 5542. https://doi.org/10.1038/s41467-020-19198-7
, 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. Wieczorek, Aleksander, & Entropy, 22(2), 131. https://doi.org/10.3390/e22020131
. (2020). On the Difference between the Information Bottleneck and the Deep Information Bottleneck. Wieser, Mario, Parbhoo, Sonali, Wieczorek, Aleksander, & Inverse Learning of Symmetries (Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M. F.; Lin, H., Ed.). Curran Associates, Inc.
. (2020). Wieser, Mario, Parbhoo, Sonali, Wieczorek, Aleksander, & Inverse learning of symmetries. 2020-December.
. (2020). Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Kindle, Ryan, Celi, Leo A., Zazzi, Maurizio, Proceedings of the ... AAAI Conference on Artificial Intelligence, 34. https://doi.org/10.1609/aaai.v34i04.6112
, & Doshi-Velez, Finale. (2020). Regional Tree Regularization for Interpretability in Deep Neural Networks. Wu, Mike, Parbhoo, Sonali, Hughes, Michael C., Kindle, Ryan, Celi, Leo, Zazzi, Maurizio, Regional tree regularization for interpretability in deep neural networks. null, 6413–6421.
, & Doshi-Velez, Finale. (2020). Chaturvedi, M., Yilmaz, R., Gschwandtner, U., Greulich, K., Reimold, M., Fuhr, P., Clinical Neurophysiology, 130(8), e122–e123. https://doi.org/10.1016/j.clinph.2019.04.614
, 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]. Bachmann, Nadine, von Siebenthal, Chantal, Vongrad, Valentina, Turk, Teja, Neumann, Kathrin, Beerenwinkel, Niko, Bogojeska, Jasmina, Fellay, Jaques, Nature Communications, 10. https://doi.org/10.1038/s41467-019-10884-9
, 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. Chaturvedi, Menorca, Bogaarts, Jan Guy, Kozak Cozac, Vitalii V., Hatz, Florian, Gschwandtner, Ute, Meyer, Antonia, Fuhr, Peter, & 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
. (2019). Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson’s disease. Keller, Sebastian Mathias, Murezzan, Damian, & 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
. (2019). Keller, Sebastian Mathias, Samarin, Maxim, Wieser, Mario, & Lecture Notes in Computer Science. Springer International Publishing. https://doi.org/10.1007/978-3-030-33676-9_12
. (2019). Deep Archetypal Analysis. In Fink, Gernot A.; Frintrop, Simone; Jiang, Xiaoyi (Ed.), Kortylewski, Adam, Wieczorek, Aleksander, Wieser, Mario, Blumer, Clemens, Parbhoo, Sonali, Morel-Forster, Andreas, Greedy Structure Learning of Hierarchical Compositional Models. https://doi.org/10.1109/cvpr.2019.01188
, & Vetter, Thomas. (2019, January 1). Wieczorek, Aleksander, & Entropy, 21(10), 975. https://doi.org/10.3390/e21100975
. (2019). Information Theoretic Causal Effect Quantification. Bogaarts, J. G., Chaturvedi, M., Cozac, V., Gschwandtner, U., Hardmeier, M., Hatz, F., Meyer, A., Fuhr, P., & Clinical Neurophysiology, 129(8), e79. https://doi.org/10.1016/j.clinph.2018.04.671
(2018). P30. A novel application of the Phase-lag-Index in functional connectivity research [Journal-article]. Chaturvedi, M., Bogaarts, J. G., Hatz, F., Cozac, V., Meyer, A., Gschwandtner, U., Liepelt-Scarfone, I., Babiloni, C., Fuhr, P., & Clinical Neurophysiology, 129(8), e99. https://doi.org/10.1016/j.clinph.2018.04.710
(2018). P78. Can Phase Lag Index (PLI) be beneficial in distinguishing Parkinsons disease Dementia (PDD) patients from Parkinsons disease (PD) patients? [Journal-article]. Cozac, V., Bogaarts, J. G., Chaturvedi, M., Gschwandtner, U., Hatz, F., Meyer, A., Clinical Neurophysiology, 129(8), e98. https://doi.org/10.1016/j.clinph.2018.04.708
, & 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]. 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
Parbhoo, Sonali, Gottesman, Omer, Ross, Andrew Slavin, Komorowski, Matthieu, Faisal, Aldo, Bon, Isabella, PloS One, 13(11), e0205839. https://doi.org/10.1371/journal.pone.0205839
, & Doshi-Velez, Finale. (2018). Improving counterfactual reasoning with kernelised dynamic mixing models. Wieczorek, Aleksander, Wieser, Mario, Murezzan, Damian, & Learning sparse latent representations with the deep copula information bottleneck. null.
. (2018). Wieser, Mario, Wieczorek, Aleksander, Murezzan, Damian, & Learning Sparse Latent Representations with the Deep Copula Information Bottleneck. https://openreview.net/forum?id=Hk0wHx-RW
. (2018, January 1). Wu, Mike, Hughes, Michael C., Parbhoo, Sonali, Zazzi, Maurizio, Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16285
, & Doshi-Velez, Finale. (2018, January 1). Wu, Mike, Hughes, Michael C., Parbhoo, Sonali, Zazzi, Maurizio, Beyond sparsity: Tree regularization of deep models for interpretability. null, 1670–1678.
, & Doshi-Velez, Finale. (2018). Chaturvedi, M., Hatz, F., Gschwandtner, U., Meyer, A., Cozac, V. V., Bogaarts, J. G., Clinical Neurophysiology, 128(10), e391–e392. https://doi.org/10.1016/j.clinph.2017.06.202
, & 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]. Chaturvedi, M., Hatz, F., Gschwandtner, U., Bogaarts, J. G., Meyer, A., Fuhr, P., & Frontiers in Aging Neuroscience, 9(3), 3. https://doi.org/10.3389/fnagi.2017.00003
(2017). Quantitative EEG (QEEG) Measures Differentiate Parkinson`s Disease Patients from Healthy Controls. Egger, Bernhard, Kaufmann, Dinu, Schönborn, Sandro, Communications in Computer and Information Science, 693, 95–112. https://doi.org/10.1007/978-3-319-64870-5_5
, & Vetter, Thomas. (2017). Copula Eigenfaces with Attributes: Semiparametric Principal Component Analysis for a Combined Color, Shape and Attribute Model. Parbhoo, Sonali, Bogojeska, Jasmina, Zazzi, Maurizio, Amia Summits on Translational Science Proceedings, 2017, 239–248. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543338/
, & Doshi-Velez, Finale. (2017). Combining Kernel and Model Based Learning for HIV Therapy Selection. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10496 LNCS.
, & Vetter, Thomas. (2017). Preface. 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
Dazert, E., Colombi, M., Boldanova, T., Moes, S., Adametz, D., Quagliata, L., Proceedings of the National Academy of Sciences of the United States of America, 113(5), 1381–1386. https://doi.org/10.1073/pnas.1523434113
, 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. Egger, Bernhard, Kaufmann, Dinu, Schönborn, Sandro, Copula Eigenfaces - Semiparametric Principal Component Analysis for Facial Appearance Modeling. https://doi.org/10.5220/0005718800480056
, & Vetter, Thomas. (2016, January 1). Kaufmann, Dinu, Parbhoo, Sonali, Wieczorek, Aleksander, Keller, Sebastian, Adametz, David, & Proceedings of Machine Learning Research, 51. http://jmlr.org/proceedings/papers/v51/kaufmann16.html
. (2016). Bayesian Markov Blanket Estimation. Kaufmann, Dinu, Parbhoo, Sonali, Wieczorek, Aleksander, Keller, Sebastian, Adametz, David, & Bayesian markov blanket estimation. null, 333–341.
. (2016). Makowska, Zuzanna, Boldanova, Tujana, Adametz, David, Quagliata, Luca, Quagliata, Luca, Vogt, Julia E., Dill, Michael T., Matter, Mathias S., The Journal of Pathology : Clinical Research, 2(2), 80–92. https://doi.org/10.1002/cjp2.37
, Terracciano, Luigi, & Heim, Markus H. (2016). Gene expression analysis of biopsy samples reveals critical limitations of transcriptome-based molecular classifications of hepatocellular carcinoma. Makowska, Z., Boldanova, T., Adametz, D., Quagliata, L., Vogt, J. E., Dill, M. T., Matter, M. S., Journal of Hepatology, 62, S424–S425. https://doi.org/10.1016/s0168-8278(15)30524-9
, 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]. Adametz, David, & Distance-based network recovery under feature correlation. 9370, 209–210.
. (2015). Alewell, Christine, Meusburger, Katrin, Kandl, Daniela, Fetai, Ilir, 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.
, Rugolo, Valentino, Schuldt, Heiko, & Vetter, Thomas. (2015). Vogt, Julia E., Kloft, Marius, Stark, Stefan, Raman, Sudhir S., Prabhakaran, Sandhya, Machine Learning, 100(2-3), 635–654. https://doi.org/10.1007/s10994-015-5516-x
, & Raetsch, Gunnar. (2015). Probabilistic clustering of time-evolving distance data. Kaufmann, Dinu, Keller, Sebastian, & Pattern Recognition (pp. 117–128). Springer. https://doi.org/10.1007/978-3-319-24947-6_10
. (2015). Copula Archetypal Analysis. In Gall, Juergen; Gehler, Peter; Leibe, Bastian (ed.), 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
Bousleiman, Habib, Zimmermann, Ronan, Ahmed, Shaheen, Hardmeier, Martin, Hatz, Florian, Schindler, Christian, Annals of Clinical and Translational Neurology, 1(11), 884–890. https://doi.org/10.1002/acn3.129
, Gschwandtner, Ute, & Fuhr, Peter. (2014). Power spectra for screening parkinsonian patients for mild cognitive impairment. 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, Journal of Clinical Investigation, 124(4), 1568–1581. https://doi.org/10.1172/jci70408
, & Heim, Markus H. (2014). Pegylated IFN-α regulates hepatic gene expression through transient Jak/STAT activation. 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., Journal of Hepatology, 60, S1–S22. https://doi.org/10.1016/s0168-8278(14)60049-0
, & 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. 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., Nucleic Acids Research, 42(14), e115. https://doi.org/10.1093/nar/gku537
, Beerenwinkel, Niko, & Metzner, Karin J. (2014). Full-length haplotype reconstruction to infer the structure of heterogeneous virus populations. Prabhakaran, Sandhya, Rey, Melanie, Zagordi, Osvaldo, Beerenwinkel, Niko, & IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), 182–191. https://doi.org/ea017b9f-ec09-4077-85ab-ded3af538c48
. (2014). HIV Haplotype Inference Using a Propagating Dirichlet Process Mixture Model. Prabhakaran, Sandhya, Rey, Melanie, Zagordi, Osvaldo, Beerenwinkel, Niko, & IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11, 182–191. https://doi.org/10.1109/tcbb.2013.145
. (2014). HIV haplotype inference using a propagating dirichlet process mixture model. Rey, Melani, Sparse meta-Gaussian information bottleneck (Jebara,Tony;Xing,Eric P., Ed.). Curran. http://jmlr.org/proceedings/papers/v32/rey14.pdf
, & Fuchs, Thomas. (2014). Adametz, David, Rey, Melanie, & Pattern recognition: 36th German Conference (p. S. 81–91). Springer International Publishing. https://doi.org/10.1007/978-3-319-11752-2_7
. (2014). Information Bottleneck for Pathway-Centric Gene Expression Analysis. In Jiang, X; Hornegger, J; Koch, R (Ed.), Adametz, David, & 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
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