3 papers
physics.chem-ph2026
Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces
Domiziano Doria, Matteo Becchi, Giovanni M. Pavan
Understanding the physics of many-body complex dynamical systems may be a non-trivial task. High-dimensional analysis approaches are often deemed necessary to prevent losing import…
cond-mat.mtrl-sci2024
A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant information
Simone Martino, Domiziano Doria, Chiara Lionello +2
Reconstructing the physical complexity of many-body dynamical systems can be challenging. Starting from the trajectories of their constitutive units (raw data), typical approaches…
physics.data-an2024
Data-driven assessment of optimal spatiotemporal resolutions for information extraction in noisy time series data
Domiziano Doria, Simone Martino, Matteo Becchi +1
In general, comprehension of any type of complex system depends on the resolution used to examine the phenomena occurring within it. However, identifying a priori, for example, the…