Information-theoretic-based measures have been useful in quantifying network complexity.
Here we briefly survey and contrast (algorithmic) information-theoretic methods which have …

We investigate the properties of a Block Decomposition Method (BDM), which extends the
power of a Coding Theorem Method (CTM) that approximates local estimations of …

Complex behaviour emerges from interactions between objects produced by different
generating mechanisms. Yet to decode their causal origin (s) from observations remains one …

Lysine 2-hydroxyisobutyrylation is a novel detected post translational modification type in
the research of proteomics. Such modification research may be helpful to several diseases' …

In estimating the complexity of objects, in particular, of graphs, it is common practice to rely
on graph-and information-theoretic measures. Here, using integer sequences with …

We apply the tensor train (TT) decomposition to construct the tensor product polynomial
chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with …

Unconventional computing is about breaking boundaries in thinking, acting and computing.
Typical topics of this non-typical field include, but are not limited to physics of computation …

Providing objective metrics of conscious state is of great interest across multiple research
and clinical fields—from neurology to artificial intelligence. Here we approach this challenge …

The concept of function arises at all levels of biological study and is often loosely and
variously defined, especially within ecology. This has led to ambiguity, obscuring the …

We introduce and develop a method that demonstrates that the algorithmic information
content of a system can be used as a steering handle in the dynamical phase space, thus …