Publications from our Researchers

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.  


BibTex format

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 = {},
volume = {2},
year = {2021}

RIS format (EndNote, RefMan)

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 -
UR -
UR -
VL - 2
ER -