I am Mario Wieser and I received my bachelor degree in computer science from HFU Furtwangen in 2012. From 2012 to 2013, I was a research assistant in the Smart Grids group at Fraunhofer Institute for Solar Energy Systems (ISE) in Freiburg. In 2015, I obtained the master degree in computer science with a focus on software engineering and cognitive systems from Karlsruhe Institute of Technology (KIT). Subsequently, I joined the Biomedical Data Analysis group at University of Basel to work towards the PhD degree. I am part of both the SystemsX.ch HIV-X and the NCCR MARVEL project and my research interests include both Bayesian and Bayesian Deep Learning for probabilistic modeling and inference in order to solve high-dimensional biomedical problems. Apart from research, I enjoy traveling and playing football.
University of Basel
Department of Mathematics and Computer Science
CH - 4051 Basel, Switzerland
E-mail: mario dot wieser at unibas dot ch
Phone: + 41 61 207 0542
List of Publications
Sonali Parbhoo*, Mario Wieser*, Volker Roth: Cause-Effect Deep Information Bottleneck For Incomplete Covariates (Under review), 2018. (*equal contribution)
Nadine Bachmann, Chantal von Siebenthal, Valentina Vongrad, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Jacques Fellay, Volker Roth, Yik Lim Kok, Christian Thorball, Alessandro Borghesi, Sonali Parbhoo, Mario Wieser, Jurg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Matthias Hoffmann, Enos Bernasconi, Matthias Cavassini, Roger Kouyos, Huldrych Gunthard, Karin Metzner, and Swiss HIV Cohort Study: Determinants of HIV-1 Reservoir Size and Long-Term Dynamics During Suppressive ART, Nature Communications, 2019.
Sebastian Keller, Maxim Samarin, Mario Wieser, Volker Roth: Deep Archetypal Analysis, German Conference on Pattern Recognition (GCPR), 2019.
Adam Kortylewski; Aleksander Wieczorek; Mario Wieser; Clemens Blumer; Sonali Parbhoo; Andreas Morel-Forster; Volker Roth and Thomas Vetter: Greedy Structure Learning of Hierarchical Compositional Models, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, Long Beach, USA.
Aleksander Wieczorek*; Mario Wieser*; Damian Murezzan and Volker Roth: Learning Sparse Latent Representations with the Deep Copula Information Bottleneck, International Conference on Learning Representations (ICLR), 2018, Vancouver, Canada. (*equal contribution)
Jan Clement; Mario Wieser; Pascal Benoit; Robert Kohrs; Christof Wittwer: A Modular Prototyping Hard- and Software Platform for Faster Development of Intelligent Charging Infrastructures of Electric Vehicles, IEEE International Conference on Power Engineering, Energy and Electrical Devices (POWERENG 2013), May 13-17, Istanbul, Turkey.
Sonali Parbhoo*; Mario Wieser* and Volker Roth: Estimating Causal Effects With Partial Covariates For Clinical Interpretability, NIPS ML4H Workshop 2018, Montreal, Canada. (*equal contribution)
Sonali Parbhoo*; Mario Wieser* and Volker Roth: Cause-Effect Deep Information Bottleneck For Incomplete Covariates, NIPS Causal Learning Workshop 2018, Montreal, Canada. (*equal contribution)
Adam Kortylewski*; Mario Wieser*; Andreas Morel-Forster*; Aleksander Wieczorek; Sonali Parbhoo; Volker Roth and Thomas Vetter: Informed MCMC with Bayesian Neural Networks for Facial Image Analysis, NIPS Bayesian Deep Learning Workshop 2018, Montreal, Canada. (*equal contribution)
Aleksander Wieczorek*; Mario Wieser*; Damian Murezzan and Volker Roth: Deep Copula Information Bottleneck, NIPS Bayesian Deep Learning Workshop 2017, Long Beach, USA. (*equal contribution)
Mario Wieser, Sonali Parbhoo and Volker Roth: Inferring and Assembling Viral Quasispecies to Improve HIV Therapy Predictions, All Systems-X day, 2016
Sonali Parbhoo; Mario Wieser and Volker Roth: HIV Therapy Selection with Incomplete Data, NIPS workshop: Machine Learning in Healthcare, 2015
Sonali Parbhoo; Mario Wieser and Volker Roth: HIV Host-Virus Interaction Networks and Implications for Treatment Design, All Systems-X day, 2015