We summarize the group's main research output in form of presentations, workshops and posters (since 2018). The list here is representative of our work but by no means exhaustive.

For (peer-reviewed journal) publications with R. Furrer as (co-)author, see also publication summary, arXiv or ZORA. Software output is listed here.

Hemri, S., Hewson, T., Gascón, E., Rajczak, J., Bhend, J., Spirig, C., Moret, L., and Liniger M. A.: How do ecPoint precipitation forecasts compare with postprocessed multi-model ensemble predictions over Switzerland? ECMWF Tech Memo, Reading, UK. https://www.ecmwf.int/node/20459

Furrer, R.: Asymptotic properties of truncated-ML estimators based on covariance approximations. Compstat 2022, Bologna, Slides

Lakatos, M., Lerch, S., Hemri, S., & Baran, S.: Comparison of multivariate post-processing methods using global ECMWF ensemble forecasts. arXiv preprint, https://arxiv.org/pdf/2206.10237

Hemri, S., Bhend, J., Spirig, C., Nerini, D., Moret, L., Furrer, R., and Liniger, M. A.: Postprocessing of gridded precipitation forecasts using conditional generative adversarial networks and quantile regression, EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022, EGU22-5609,  https://doi.org/10.5194/egusphere-egu22-5609

Hemri, S., Dai, Y., Bhend, J., Spirig, C., Nerini, D., Furrer, R., Moret, L. and Liniger, M. A.: Spatially coherent postprocessing of cloud cover and precipitation forecasts using generative adversarial networks, ECMWF Machine Learning Workshop, online, 29 March - 1 April 2022,  Slides

Hemri, S., Bhend, J., Spirig, C., Furrer, R., Moret, L., and Liniger, M. A.: Spatially consistent postprocessing of precipitation over complex topography , EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-129, https://doi.org/10.5194/ems2021-129.

Furrer, R: Computational Reproduciblilty, DACH Epidemiologietagung, 1. - 3. September 2021, Bern, CH. Slides.

Furrer, R, Flury, R. and Blasi. F. Spatial Statistics for Huge Datasets and Best Practices, useR! 2021 Conference, online, https://www.youtube.com/watch?v=gQEM-cpLrmg.

Cherneva, K., Furrer, R. and Tarigan, B.: SampleSizeR: calculate sample sizes within completely randomized design, doi: 10.17605/OSF.IO/NF9P2 [online]. Available at: http://shiny.math.uzh.ch/git/reinhard.furrer/SampleSizeR/

Tarigan, B.: Planning Experiments and Sample Size Calculations, StatsBrief.

Tarigan, B. and Cherneva, K.: Sample Size Calculation for one-way ANOVA with Repeated Measures in Time, StatsBrief.

Tarigan, B.: Comparing survival curves, StatsBrief.

Dai, Y. and Hemri, S.: Spatially coherent postprocessing of cloud cover forecasts using generative adversarial networks, EGU General Assembly 2021, online, 19-30 Apr 2021, EGU21-4374, https://doi.org/10.5194/egusphere-egu21-4374

Brunner, M. I., Furrer, R., and Gilleland, E.: Functional data clustering as a powerful tool to group streamflow regimes and flood hydrographs, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-375, https://doi.org/10.5194/egusphere-egu21-375.

Dambon, J. A.: Gaussian Process-based Spatially Varying Coefficient Models, Kernel Club, Colorado School of Mines, Presentation. Slides.

Furrer, R.: How to Peer Review. Presentation for the EpiBiostat PhD Program. Recorded presentation (uncut).

Dambon, J.: varycoef: Modeling Spatially Varying Coefficients. eRum 2020, virtual conference. Presentation. Slides.

Flury, R.: Identification of Dominant Features in Spatial Data. Research in progress talk. Slides.

Staudinger, M., Furrer, R. and Viviroli, D.: A framework to characterize flood events of defined return period ranges using functional boxplots, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU2020-9950, https://doi.org/10.5194/egusphere-egu2020-9950.

Dambon, J. A., Fahrländer, S. S., Karlen, S., Lehner, M., Schlesinger, J., Sigrist, F., Zimmermann, A.: Examining the Vintage Effect in Hedonic Pricing using Spatially Varying Coefficients Models: A Case Study of Single-Family Houses in the Canton of Zurich, Preprint, ResearchGate.

Dambon, J. A.: organization and chairing of invited topic-contributed session “Advances in Disease Mapping” at Joint Statistical Meetings 2020, virtual conference, Session Info.

Dambon, J.: varycoef: An R Package to Model Spatially Varying Coefficients. Swiss Statistics Seminar, Bern, Switzerland. Poster.

Furrer, R.: Interpolation for huge spatial datasets: theory, implementations and ideas. University of Geneva, Presentation.

Flury, R.: A Spatial Field Decomposition Approach to Evaluate Biodiversity Indices on Dominant Scales. JSM Denver, USA, Presentation. Slides.

Dambon, J.: Spatially Varying Coefficients Models: How MLE Stacks up Against Other Methods. JSM Denver, USA, Presentation. Slides.

Furrer, R.: Scalable gapfilling in spatio- temporal remote sensing data. JSM Denver, USA, Presentation. Slides.

Flury, R.: Multiresolution Decomposition of Areal Count Data, Graspa 2019. Pescara, It. Poster.

Schuh, L.: Advancing Methods to Model Landscape Heterogeneity. Global Change and Biodiversity: Integrating the impact of earth and world drivers across scales, Monte Verità, Switzerland. Poster.

Dambon, J.: Spatially Varying Coefficients Models for Large Data using MLE. Spatial Statistics 2019, Sitges, S. Presentation.

Furrer, R.: Modeling and prediction of extreme events over networks. Workshop on "Causality and Extremes", Presentation. Slides.

Furrer, R.: Share your Code?. EBPI colloquium , Discussion. Slides.

Kratzer, G.: Regression models, mixed models and and introduction to ggplot: good scientific practice for Neuroscientists using R programming language. In: Advanced statistics workshop, University of Zurich, Feb. 6th. and 7th. Presentation in Workshop.

Furrer, R.: Interpolation for huge spatial datasets: theory, implementations and ideas. Department of Statistics, University of Uppsala, Sweden, Jan. 30th. Invited seminar talk. Slides.

Kratzer, G.: Bayesian Networks meet Observational data. 1st Causality workshop, Zurich University, Switzerland, Dec. 4th. Workshop (Main Organizer). Slides.

Furrer, R.: The Power and Limits of Statistics. 2-day Molecular Life Sciences PhD Programme Course "Different perspectives on Responsible Research and Good Scientific Practice", Nov. 12th. Presentation. Slides.

Furrer, R.: Imputing missing values in satellite data: From parametric to non-parametric approaches. Institute for Geoinformatics, University of Münster, Nov. 13th. Invited seminar talk. Slides.

Kratzer, G.: Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology. Swiss Statistical Society, Bern University, Switzerland, Nov. 9th. 2018. Poster.

Dambon, J.: Spatially Varying Coefficients Models: A Comparison of Maximum Likelihood Estimators with other Estimators. Swiss Statistics Seminar 2018, University of Bern, Switzerland, Nov.9th. Poster.

Kratzer, G.: Multivariable analysis: variable and model selection in system epidemiology. Danone, Utrecht, the Netherlands, Oct. 4th. 2018. Invited seminar talk. Slides.

Furrer, R.: Imputing missing values in satellite data: From parametric to non-parametric approaches. Department of Statistics and Operations Research, Public University of Navarre, Spain, Sept. 26th. Invited seminar talk. Slides.

Kratzer, G.: Academical statistical consulting service for veterinary research and case study about ethic and statistics. M-14E Current topics of Laboratory Animal Science, University of Zurich, Sep. 14th. Presentation in Workshop.

Wang, C.: Generalised Spatial Fusion Model Framework for Multivariate Analysis of Point and Areal Data. GeoEnv2018, Belfast, July 4th. Presentation. Slides.

Kratzer, G.: Comparison between Suitable Priors for Additive Bayesian Networks. BAYSM 2018, University of Warwick, United Kingdom, Jul. 2nd. 2018. Poster.

Furrer, R.: Predicting missing values in spatio-temporal satellite data. ISNPS 2018, Salerno, June 14th. Presentation in Invited Session. Slides.

Kratzer, G.: Bayesian Networks Learning in a Nutshell. Brown Bag Seminar at ZHAW, Winterthur, Switzerland, May 30th. Invited seminar talk. Slides.

Kratzer, G.: Advances in Additive Bayesian Network applied to observational systems epidemiology datasets. Institute of Global Health, Geneva University, Switzerland, May 2nd. Invited seminar talk. Slides.

Schuh, L.: Regional climate regulation by different land cover types: comparing homogeneous and heterogeneous structures in agricultural landscapes. EGU, Vienna. Poster.

Kratzer, G.: Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology. Society for Veterinary Epidemiology and Preventive Medicine (SVEPM), Tallinn, Estonia, Mar. 22th. 2018. Poster.