455 citations · 2.7k across the 72 of their papers we have counts for
74 papers
CYNAR: a trajectory-based estimator of entropy production
Marco Baiesi, Ivan DI Terlizzi
Inferring the entropy production rate from recorded trajectories is a key challenge in stochastic thermodynamics. In experiments, the forces governing the dynamics are usually…
Variance sum rule: proofs and solvable models
Ivan Di Terlizzi, Marco Baiesi, Felix Ritort
We derive, in more general conditions, a recently introduced variance sum rule (VSR) [I. Di Terlizzi et al., 2024 Science 383 971] involving variances of displacement and force imp…
Constrained hidden Markov models reveal further Hsp90 protein states
Riccardo Tancredi, Antonio Feltrin, Giosuè Sardo Infirri +4
Time series of conformational dynamics in proteins are usually evaluated with hidden Markov models (HMMs). This approach works well if the number of states and their connectivity i…
Effective estimation of entropy production with lacking data
Marco Baiesi, Tomohiro Nishiyama, Gianmaria Falasco
Observing stochastic trajectories with rare transitions between states, practically undetectable on time scales accessible to experiments, makes it impossible to directly quantify…
Interpretable machine learning of amino acid patterns in proteins: a statistical ensemble approach
Anna Braghetto, Enzo Orlandini, Marco Baiesi
Explainable and interpretable unsupervised machine learning helps understand the underlying structure of data. We introduce an ensemble analysis of machine learning models to conso…
Variance Sum Rule for Entropy Production
I. Di Terlizzi, M. Gironella, D. Herraez-Aguilar +4
Entropy production is the hallmark of nonequilibrium physics, quantifying irreversibility, dissipation, and the efficiency of energy transduction processes. Despite many efforts, i…