We will discuss about "RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy", Behrendt et al., SoftwareX, 2019 Abstract: This paper shows how to quantify and test for the information flow between two time series with Shannon transfer entropy and Rényi transfer entropy using the R package RTransferEntropy. We discuss the methodology, the bias …

We will discuss about "A topological data analysis based classifier", Kindelan et al., arXiv, 2022 Abstract: Topological Data Analysis is an emergent field that aims to discover the underlying dataset’s topological information. Topological Data Analysis tools have been commonly used to create filters and topological descriptors to improve Machine Learning (ML) methods. This paper proposes …

We will discuss about "An Efficient Characterization of Complex-Balanced, Detailed-Balanced, and Weakly Reversible Systems", Craciun et al., SIAM Journal on Applied Mathematics, 2020 Abstract: Very often, models in biology, chemistry, physics, and engineering are systems of polynomial or power-law ordinary differential equations, arising from a reaction network. Such dynamical systems can be generated by many …

We will discuss about "Toroidal topology of population activity in grid cells", Gardner et al., Nature, 2021. Abstract: The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations, …

We will discuss about "The 103,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes", Katori et al., PNAS, 2022. Abstract: Human sleep phenotypes can be defined and diversified by both genetic and environmental factors. However, some sleep phenotypes are difficult to evaluate without long-term, precise sleep monitoring, for which simple …