Information field theory and artificial intelligence
T Enßlin - Entropy, 2022 - mdpi.com
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 …
for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and …
An information field theory approach to Bayesian state and parameter estimation in dynamical systems
K Hao, I Bilionis - Journal of Computational Physics, 2024 - Elsevier
Dynamical system state estimation and parameter calibration problems are ubiquitous
across science and engineering. Bayesian approaches to the problem are the gold standard …
across science and engineering. Bayesian approaches to the problem are the gold standard …
Neural information field filter
K Hao, I Bilionis - arXiv preprint arXiv:2407.16502, 2024 - arxiv.org
We introduce neural information field filter, a Bayesian state and parameter estimation
method for high-dimensional nonlinear dynamical systems given large measurement …
method for high-dimensional nonlinear dynamical systems given large measurement …
Analysis of Dynamical Field Inference in a Supersymmetric Theory
The inference of dynamical fields is of paramount importance in science, technology, and
economics. Dynamical field inference can be based on information field theory and used to …
economics. Dynamical field inference can be based on information field theory and used to …
An information field theory approach to engineering inverse problems
A Alberts - 2024 - search.proquest.com
Inverse problems in infinite dimensions are ubiquitously encountered across the scien-tific
disciplines. These problems are defined by the need to reconstruct continuous fields from …
disciplines. These problems are defined by the need to reconstruct continuous fields from …