Valais/Wallis AI Workshop 2nd edition

Data-driven approaches are increasingly used in support of scientific, technological and economical activities.
Yet, in many situations the amount of data is drastically limited due to time and cost constraints, feasibility, and intrinsic rarity. This includes notably:

* Ecological and medical studies, where observations of rare species/pathologies are scarce

* Catastrophe modelling (related to waste storage, climate evolution, financial crises, etc.) where samples are small or even void due, e.g., to extreme conditions or large time-scales

* Resource-intensive experiments performed on natural and artificial systems, e.g. in protein synthesis, in robot calibration, or in hi-fidelity simulation-based design

In this second Valais/Wallis Artificial Intelligence (AI) Workshop, we will focus on several facets of such challenging topics, which will be tackled through presentations from several leading Swiss-based researchers having to cope with small data with motivating applications in environment and geosciences, medicine, energy engineering, robotics and beyond. In this context, general and domain-specific topics in visualization and extraction of relevant features from small and big data will also be discussed.

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