5 citations · 9 across the 3 of their papers we have counts for
4 papers
Learning the information contained in the microstructure of data distributions
Lucrezia L. Baldo, Chiara Lionello, Edward D. Donkor +2
Understanding how much and where information is nested in sets of data obtained using different parameters and metrics is a typical problem in the analysis of high-dimensional data…
dynsight: an Open Python Platform for Simulation and Experimental Trajectory Data Analysis
Simone Martino, Matteo Becchi, Andrew Tarzia +2
The study of complex many-body systems via analysis of the trajectories of the units that dynamically move and interact within them is a non-trivial task. The workflow for extracti…
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…
Relevant, hidden, and frustrated information in high-dimensional analyses of complex dynamical systems with internal noise
Chiara Lionello, Matteo Becchi, Simone Martino +1
Extracting from trajectory data meaningful information to understand complex molecular systems might be non-trivial. High-dimensional analyses are typically assumed to be desirable…