A physical field has an infinite number of degrees of freedom since it has a field value at
each location of a continuous space. Therefore, it is impossible to know a field from finite …

The statistical inference of the state variable and the drift function of stochastic differential
equations (SDE) from sparsely sampled observations are discussed herein. A variational …

Information field theory (IFT), the information theory for fields, is a mathematical framework
for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and …

Approximate solutions of the chemical master equation and the chemical Fokker-Planck
equation are an important tool in the analysis of biomolecular reaction networks. Previous …

There exists various proposals to detect cosmic strings from Cosmic Microwave Background
(CMB) or 21 cm temperature maps. Current proposals do not aim to find the location of …

Markov jump process models have many applications across science. Often these models
are defined on a state space of product form and only one of the components of the process …

Reputation is a central element of social communications, be it with human or artificial
intelligence (AI), and as such can be the primary target of malicious communication …

Quantitatively predictive models of biomolecular circuits are important tools for the design of
synthetic biology and molecular communication circuits. The information content of typical …

Gaussian Processes (GPs) are highly expressive, probabilistic models. A major limitation is
their computational complexity. Naively, exact GP inference requires $\mathcal {O}(N^ 3) …

Modern day Bayesian imaging problems in astrophysics as well as other scientific areas
often result in non-Gaussian and very high-dimensional posterior probability distributions as …