WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models

2 May 2022

Papers citing "WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models"

7 / 7 papers shown

Title
Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán A. Charlton-Perez H. Dacre Simon Driscoll Suzanne L. Gray Ben Harvey ... Kieran M. R. Hunt Robert W. Lee Ranjini Swaminathan R. Vandaele Ambrogio Volonté AI4Cl 38 29 0 05 Dec 2023
WeatherBench 2: A benchmark for the next generation of data-driven global weather models S. Rasp Stephan Hoyer Alexander Merose I. Langmore Peter W. Battaglia ... Carla Bromberg Jared Sisk Luke Barrington Aaron Bell Fei Sha AI4Cl 32 107 0 29 Aug 2023
Inductive biases in deep learning models for weather prediction Jannik Thümmel Matthias Karlbauer S. Otte C. Zarfl Georg Martius ... Thomas Scholten Ulrich Friedrich V. Wulfmeyer B. Goswami Martin Volker Butz AI4CE 43 5 0 06 Apr 2023
Workload Forecasting of a Logistic Node Using Bayesian Neural Networks Emin Cagatay Nakilcioglu Anisa Rizvanolli 21 1 0 09 Nov 2022
SwinVRNN: A Data-Driven Ensemble Forecasting Model via Learned Distribution Perturbation Yuan Hu Lei Chen Zhibin Wang Hao Li OOD 29 47 0 26 May 2022
MetNet: A Neural Weather Model for Precipitation Forecasting C. Sønderby L. Espeholt Jonathan Heek Mostafa Dehghani Avital Oliver Tim Salimans Shreya Agrawal Jason Hickey Nal Kalchbrenner AI4Cl 231 273 0 24 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015