Combining Causal Inference and Extreme Value Theory in the Study of Climate Extremes and their Causes
Videos from BIRS Workshop
Aurélien Ribes, Météo France - CNRS
Monday Jun 27, 2022 07:45 - 08:45
Overview on Climatology
Anthony Davison, Ecole Polytechnique Fédérale de Lausanne (EPFL)
Monday Jun 27, 2022 09:00 - 10:00
Overview on Extreme Value Theory
Linbo Wang, University of Toronto
Monday Jun 27, 2022 10:15 - 11:15
Overview on Causal Inference
Manuela Brunner, ETH Zurich and SLF Davos
Tuesday Jun 28, 2022 07:45 - 08:15
Classification reveals varying drivers of severe and moderate hydrological droughts in Europe
Maud Thomas, Sorbonne University
Tuesday Jun 28, 2022 08:30 - 09:00
Non-asymptotic bounds for probability weighted moment estimators
Thordis Thorarinsdottir, Norwegian Computing Center
Tuesday Jun 28, 2022 09:30 - 10:00
Consistent estimation of extreme precipitation and flooding across multiple durations
Gloria Buriticá, Sorbonne Université
Tuesday Jun 28, 2022 10:15 - 10:45
Assessing time dependencies for heavy rainfall modeling
Jonathan Jalbert, Polytechnique Montréal
Tuesday Jun 28, 2022 10:45 - 11:15
Frequency analysis of projected discharges on ungauged river sections using a large set of hydrological simulations
Dáithí Stone, National Institute of Water & Atmospheric Research Ltd (NIWA)
Tuesday Jun 28, 2022 11:15 - 11:45
The effect of experiment conditioning on estimates of human influence on extreme weather
Anna Kiriliouk, Université de Namur
Wednesday Jun 29, 2022 07:15 - 07:45
Estimating failure probabilities for high-dimensional extremes
Claudia Klüppelberg, TU Munich
Wednesday Jun 29, 2022 07:45 - 08:15
Max-linear Bayesian networks
Mario Krali, École polytechnique fédérale de Lausanne
Wednesday Jun 29, 2022 08:15 - 08:45
Detecting max-linear structural equation models in extremes
Andreas Gerhardus, German Aerospace Center
Wednesday Jun 29, 2022 09:00 - 09:30
Numerical study of constraint-based time series causal discovery algorithms on synthetic data with heavy-tailed noise distributions
Leonard Henckel, University of Copenhagen
Wednesday Jun 29, 2022 09:30 - 10:00
HSIC-X: an estimator exploiting independent instruments
Dan Cooley, Colorado State University
Wednesday Jun 29, 2022 10:15 - 10:45
Transformed Linear Prediction for Extremes
Emma Simpson, University College London
Wednesday Jun 29, 2022 10:45 - 11:15
Capturing varied extremal dependence structures via mixtures of conditional extremes models
Richard Smith, University of North Carolina Chapel Hill
Wednesday Jun 29, 2022 11:15 - 11:45
Modeling Trends in Spatial Extremes and their Causal Determination
Raphael Huser, King Abdullah University of Science and Technology
Thursday Jun 30, 2022 07:15 - 07:45
Identifying US wildfire drivers using partially-interpretable neural networks for high-dimensional extreme quantile regression
Yan Gong, KAUST
Thursday Jun 30, 2022 07:45 - 08:15
Partial tail correlation coefficient applied to extremal network learning
Juraj Bodík, University of Lausanne
Thursday Jun 30, 2022 08:15 - 08:45
Causal inference for Extreme dependence
Sebastian Engelke, University of Geneva
Thursday Jun 30, 2022 09:00 - 09:30
Estimation and Inference of Extremal Quantile Treatment Effects
Nicola Gnecco, University of Geneva
Thursday Jun 30, 2022 09:30 - 10:00
Causal discovery in heavy-tailed models
Mila Sun, McGill University
Thursday Jun 30, 2022 10:00 - 10:30
Principal stratification for quantile causal effects under partial compliance
Jevenijs Ivanovs, Aarhus University
Thursday Jun 30, 2022 10:45 - 11:15
Graphical models for extremes and Levy processes - a unified framework
Stanislav Volgushev, University of Toronto
Thursday Jun 30, 2022 11:15 - 11:45
Learning graphical models for extremes
