L
Lukas Geyrhofer
Researcher at Technion – Israel Institute of Technology
Publications - 19
Citations - 1460
Lukas Geyrhofer is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Population & Random walk. The author has an hindex of 10, co-authored 17 publications receiving 785 citations. Previous affiliations of Lukas Geyrhofer include Max Planck Society & ETH Zurich.
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Journal ArticleDOI
Ranking the effectiveness of worldwide COVID-19 government interventions.
Nils Haug,Lukas Geyrhofer,Alessandro Londei,Elma Dervic,Amélie Desvars-Larrive,Vittorio Loreto,Beate Pinior,Stefan Thurner,Stefan Thurner,Peter Klimek +9 more
TL;DR: The results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus, and a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools is proposed.
Journal ArticleDOI
A structured open dataset of government interventions in response to COVID-19.
Amélie Desvars-Larrive,Elma Dervic,Nils Haug,Thomas Niederkrotenthaler,Jiaying Chen,Anna Di Natale,Jana Lasser,Diana S. Gliga,Alexandra Roux,Alexandra Roux,Johannes Sorger,Abhijit Chakraborty,Alexandr Ten,Alija Dervic,Andrea Pacheco,Ania Jurczak,David Cserjan,Diana Lederhilger,Dominika Bulska,Dorontinë Berishaj,Erwin Flores Tames,Francisco S. Álvarez,Huda Takriti,Jan Korbel,Jenny Reddish,Joanna Grzymała-Moszczyńska,Johannes Stangl,Lamija Hadziavdic,Laura Stoeger,Leana Gooriah,Lukas Geyrhofer,Márcia R. Ferreira,Marta Bartoszek,Rainer Vierlinger,Samantha Holder,Simon Haberfellner,Verena Ahne,Viktoria Reisch,Vito D. P. Servedio,Xiao Chen,Xochilt Pocasangre-Orellana,Zuzanna Garncarek,David Garcia,Stefan Thurner,Stefan Thurner +44 more
TL;DR: A specific hierarchical coding scheme for NPIs is developed and a comprehensive structured dataset of government interventions and their respective timelines of implementation is generated via an open library to improve transparency and motivate collaborative validation process.
Journal ArticleDOI
Deep sequencing of a genetically heterogeneous sample: local haplotype reconstruction and read error correction.
TL;DR: A generative probabilistic model for assigning observed reads to unobserved haplotypes in the presence of sequencing errors and a Gibbs sampler for sampling from the joint posterior distribution of haplotype sequences are developed to obtain estimates of the local haplotype structure of the population.
Book ChapterDOI
Deep Sequencing of a Genetically Heterogeneous Sample: Local Haplotype Reconstruction and Read Error Correction
TL;DR: A generative probabilistic model for assigning observed reads to unobserved haplotypes in the presence of sequencing errors and a Gibbs sampler for sampling from the joint posterior distribution of haplotype sequences to obtain estimates of the local haplotype structure of the population.
Posted ContentDOI
Ranking the effectiveness of worldwide COVID-19 government interventions
Nils Haug,Lukas Geyrhofer,Alessandro Londei,Elma Dervic,Amélie Desvars-Larrive,Vittorio Loreto,Beate Pinior,Stefan Thurner,Stefan Thurner,Peter Klimek +9 more
TL;DR: It is shown that there are NPIs considerably less intrusive and costly than lockdowns that are also highly effective, such as certain risk communication strategies and voluntary measures that strengthen the healthcare system.