Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
ITS1.16/SM1.2 | Geophysical Uncertainty and Inference - Where Next?
Geophysical Uncertainty and Inference - Where Next?
Convener: Nicola Piana Agostinetti | Co-conveners: Alison Malcolm, Xin ZhangECSECS, Malcolm Sambridge
The field of geophysical inversion is critical to risk analysis and decision-making in a wide variety of geoscientific contexts, and has a long history: from the first theoretical studies focused on questions of existence, stability, and uniqueness, through nonlinear optimisation, large parameter estimation problems, to quantification of uncertainty in both parameter values and model choice. Systems studied have become larger, data set sizes have exploded, and many algorithms have been borrowed, adapted and devised anew. This session aims to explore cutting-edge methods, tools, and approaches that push the boundaries of geophysical inference and uncertainty analysis. We ask the question `Where to next?’

We invite researchers, practitioners, and experts to join us in a session focused on the future directions of geophysical uncertainty assessment and inference.

Example topics of Interest:

1. Advanced methods for Bayesian Inference: Explore the latest developments in Bayesian sampling and model choice. How do these techniques transform our ability to make robust inferences and predictions in the face of complex geophysical systems?

2. Machine Learning and related methods: Investigate the integration of machine learning and artificial intelligence in geophysical inference and uncertainty analysis. Share insights into how these technologies are influencing the future of geophysical inference via surrogate modelling, parameter estimation and uncertainty assessment.

3. Applications: Real-world examples of geophysical uncertainty assessment and inference in action, highlighting successes, challenges, and lessons learned.