Modern Statistical and Machine Learning Approaches for High-Dimensional Compound Spatial Extremes
Videos from BIRS Workshop
Douglas Nychka, Colorado School of Mines
Monday May 8, 2023 01:00 - 02:30
Short course I: Spatial Statistical Learning (co-taught with Soutir Bandyopadhyay)
Douglas Nychka, Colorado School of Mines
Monday May 8, 2023 01:00 - 02:30
Short course I: Spatial Statistical Learning (co-taught with Soutir Bandyopadhyay)
Raphael Huser, King Abdullah University of Science and Technology
Monday May 8, 2023 03:00 - 04:30
Short Course II: Advances in Statistical Modeling of Spatial Extremes
Frances Zwiers, University of Victoria
Monday May 8, 2023 06:30 - 07:00
Detection and Attribution of Human Influence on Extreme Precipitation Events
Lyndsay Shand, Sandia National Laboratories
Monday May 8, 2023 07:00 - 07:30
A Multivariate Space-Time Dynamic Model for Characterizing Downstream Impacts of the 1991 Mt Pinatubo Volcanic Eruption
Ana Cebrian, University of Zaragoza
Monday May 8, 2023 07:30 - 08:00
Spatio-Temporal Analysis of the Extent of Extreme Heat Events
Steve Sain, Jupiter Intelligence
Monday May 8, 2023 08:00 - 08:30
Extremes and Climate Risk Analytics: Some Applications and Some Open Problems
Abhi Datta, Johns Hopkins University
Tuesday May 9, 2023 01:00 - 01:30
Combining Machine Learning with Traditional Geospatial Models
Andrew Zammit Mangion, University of Wollongong
Tuesday May 9, 2023 01:30 - 02:00
Neural Point Estimation for Fast Optimal Likelihood-Free Inference
Mikael Kuusela, Carnegie Mellon University
Tuesday May 9, 2023 02:00 - 02:30
Neural Likelihood Surface Estimation for Intractable Spatial Models
Sweta Rai, Colorado School of Mines
Tuesday May 9, 2023 03:00 - 03:06
Fast Parameter Estimation of GEV Distribution Using Neural Networks
Jordan Richards, King Abdullah University of Science and Technology
Tuesday May 9, 2023 03:06 - 03:12
Neural Bayes Estimators for Fast and Efficient Inference with Spatial Peaks-Over-Threshold Models
Jonathan Koh, University of Bern
Tuesday May 9, 2023 03:12 - 03:18
Predicting Risks of Temperature Extremes using Large-scale Circulation Patterns with r-Pareto Processes
Lydia Kakampakou, Lancaster University
Tuesday May 9, 2023 03:18 - 03:24
Modelling Temporal Changes in Spatial Extremal Dependence via a Conditional Framework
Silius Mortensønn Vandeskog, The Norwegian University of Science and Technology
Tuesday May 9, 2023 03:24 - 03:30
Efficient and Robust Modelling of High-Dimensional Spatial Conditional Extremes
Xuanjie Shao, King Abdullah University of Science and Technology
Tuesday May 9, 2023 03:36 - 03:42
Deep Compositional Models for Nonstationary Extremal Dependence in Space
Lambert De Monte, The University of Edinburgh
Tuesday May 9, 2023 03:42 - 03:48
A Geometric Investigation of the Hüsler–Reiss Family of Distributions
Maggie Bailey, Colorado School of Mines
Tuesday May 9, 2023 03:48 - 03:54
Temporal Downscaling for Solar Radiation Using a Diurnal Template Model
Zhongwei Zhang, University of Geneva
Tuesday May 9, 2023 03:54 - 03:00
Extremal Dependence of Stochastic Processes Driven by Exponential-Tailed Lévy Noise
Janine Illian, University of Glasgow
Wednesday May 10, 2023 01:00 - 01:30
Realistically Complex Spatial Models – Communication and Accessibility
David Bolin, King Abdullah University of Science and Technology (KAUST)
Wednesday May 10, 2023 02:00 - 02:30
Gaussian Random Fields on Compact Metric Graphs
Sebastian Engelke, University of Geneva
Thursday May 11, 2023 01:00 - 01:30
Extremal Graphical Models: a Review of Recent Progress
Marco Oesting, Universitat Stuttgart
Thursday May 11, 2023 01:30 - 02:00
Extremes in High Dimensions
Peter Braunsteins, University of New South Wales
Thursday May 11, 2023 02:00 - 02:30
Linking SPDEs and Spatial Extremes
Simon Brown, Met Office
Thursday May 11, 2023 03:00 - 03:30
Future Changes in Heatwave Severity, Duration and Frequency due to Climate Change for the Most Populous Cities
Michael Wehner, Lawrence Berkeley Lab-Scientific Computing Group
Thursday May 11, 2023 03:30 - 04:00
Some Examples of Climate Science Machine Learning at Berkeley Lab
Finn Lindgren, University of Edinburgh
Thursday May 11, 2023 04:00 - 04:30
Statistical Climate Reconstruction Modelling in the EUSTACE Project
Emma Simpson, University College London
Thursday May 11, 2023 06:30 - 07:00
High-Dimensional Modeling of Spatial Conditional Extremes Using INLA and Gaussian Markov Random Fields
Léo Belzile, HEC Montréal
Thursday May 11, 2023 07:00 - 08:30
Modelling of Sparse Conditional Spatial Extremes Processes Subject to Left-Censoring
Jordan Richards, King Abdullah University of Science and Technology
Thursday May 11, 2023 07:30 - 08:00
High-dimensional Quantile Regression of Spatiotemporal Extreme Wildfires via Partially-Interpretable Neural Networks
Anna Kiriliouk, Université de Namur
Thursday May 11, 2023 08:30 - 09:00
Estimating Probabilities of Multivariate Failure Sets Based on Pairwise Tail Dependence Coefficients
Thomas Opitz, INRAE
Thursday May 11, 2023 09:00 - 09:30
Bridges from Spatial Extreme-value Theory to Classical Geostatistics
Likun Zhang, University of Missouri
Friday May 12, 2023 01:30 - 02:00
Emulating Complex Climate Models via Integrating Variational Autoencoder and Spatial Extremes
Yao Xie, Georgia Institute of Technology
Friday May 12, 2023 02:00 - 02:30
Spatiotemporal Point Processes with Deep Kernels
