In this section
Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@article{Medina-Mardones:2021:2632-072x/abf231,
author = {Medina-Mardones, AM and Rosas, FE and Rodríguez, SE and Cofré, R},
doi = {2632-072x/abf231},
journal = {Journal of Physics: Complexity},
pages = {1--16},
title = {Hyperharmonic analysis for the study of high-order information-theoretic signals},
url = {http://dx.doi.org/10.1088/2632-072x/abf231},
volume = {2},
year = {2021}
}
TY - JOUR
AB - Network representations often cannot fully account for the structural richness of complex systems spanning multiple levels of organisation. Recently proposed high-order information-theoretic signals are well-suited to capture synergistic phenomena that transcend pairwise interactions; however, the exponential-growth of their cardinality severely hinders their applicability. In this work, we combine methods from harmonic analysis and combinatorial topology to construct efficient representations of high-order information-theoretic signals. The core of our method is the diagonalisation of a discrete version of the Laplace–de Rham operator, that geometrically encodes structural properties of the system. We capitalise on these ideas by developing a complete workflow for the construction of hyperharmonic representations of high-order signals, which is applicable to a wide range of scenarios.
AU - Medina-Mardones,AM
AU - Rosas,FE
AU - Rodríguez,SE
AU - Cofré,R
DO - 2632-072x/abf231
EP - 16
PY - 2021///
SN - 2632-072X
SP - 1
TI - Hyperharmonic analysis for the study of high-order information-theoretic signals
T2 - Journal of Physics: Complexity
UR - http://dx.doi.org/10.1088/2632-072x/abf231
UR - https://iopscience.iop.org/article/10.1088/2632-072X/abf231
UR - http://hdl.handle.net/10044/1/90013
VL - 2
ER -
Data Science Institute
William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom
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