Interpretable frameworks integrating theory and practice

Develop interpretable frameworks for reservoir computing that integrate theoretical principles with practical implementations to enhance the prevalence, transparency, and adoption of RC across physical and digital substrates.

Background

Interpretability remains a challenge in RC, particularly for physical substrates. The paper calls for frameworks that connect theory and practice, enabling clearer understanding of reservoir dynamics and mechanisms, and thereby facilitating broader use and trust in RC methods.

References

However, many questions remain unresolved: And how can interpretable frameworks be developed to integrate theory with practice and enhance the prevalence of RC?

— Robustly optimal dynamics for active matter reservoir computing (2505.05420 - Gaimann et al., 8 May 2025) in Section 1 (Introduction)