… that the bottleneck variable learned in SPIB tries to carry the maximum information of the
state-… separation between the state-to-state transitions and the fluctuations within metastable …

… In this work, we focus on the recently developed artificial intelligence-based State Predictive
Information Bottleneck (SPIB) approach and demonstrate how SPIB can learn such a …

… predictive information from incoming temporal signals is crucial for two reasons. First,
predictive … We now state the past-future information bottleneck of dynamical systems PFIB. The …

… Recently, predictive information was proposed … information theoretic approach to predictive
inference taken in the present paper is based on a simple extension of predictive information (…

… Moreover, the clustering is particularly tight for nonlinear IB, meaning that the bottleneck
states carry almost no information about input vectors beyond class identity. Note that in this …

… -State Predictive Information Bottleneck (GNN-SPIB) framework, which combines graph neural
networks and the state predictive information bottleneck to … and kinetic information for slow …

… Thus, the information that contains about is squeezed through a compact “bottleneck”, …
This thesis first reviews in detail the Information Bottleneck (IB) approach and its relations to …

… Employing a one-dimensional reaction coordinate derived from the State Predictive Information
Bottleneck framework, our simulations capture back-and-forth phase transitions across …

… of state. In this paper, we propose an information-theoretic dynamic bottleneck objective
with a predictable parametric prior, which preserves and compresses predictive information …

… For this we use the Predictive Information Bottleneck framework used for the first two …
complex yet most predictive aspects of a given biomolecular trajectory. This information is used to …