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 the SystemsX.ch HIV-X 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)
Adam Kortylewski; Clemens Blumer; Aleksander Wieczorek; Mario Wieser; Sonali Parbhoo; Andreas Morel-Forster; Volker Roth and Thomas Vetter: Greedy Structure Learning of Hierarchical Compositional Models (Under review), 2018.
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) (to appear), 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