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Machine Learning for Atmospheric Science and Ear ... (No replies)
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Atmospheric science and earth observations are data-rich environments, in which a variety of instruments and simulation techniques produce heterogenous data sets. The MACLEAN workshop brings together machine learners and domain experts to facilitate machine-learning solutions in atmospheric science and earth observations. The workshop provides an overview over current machine-learning applications and fosters exchange and knowledge transfer to develop new machine learning solutions. The MACLEAN workshop is part of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2023) in Turin, Italy.
IMPORTANT INFORMATION
Machine Learning for Earth Observation (MACLEAN) workshop
Turin, Italy, 18 or 22 September 2023
Workshop website: https://sites.google.com/view/maclean23/
The workshop is part of ECML PKDD 2023 (https://2023.ecmlpkdd.org/)
KEY DATES
12 June 2023: Paper submission.
12 July 2023: Notification of acceptance.
TOPICS
The non-exclusive list of topics for the workshop includes:
Supervised and unsupervised machine learning methods
Semi-supervised classification, domain adaptation, active learning, structured output learning, multi-task learning, and online learning
Interpretability and explainability of machine learning methods
Bayesian modelling of various parts of EO or atmospheric processes
Dimensionality reduction and feature selection, finding embeddings and latent variables
Visualisation and interaction with EO and atmospheric data
Interactive model building and eliciting expert knowledge
Applications of high-performance computing