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Found 8 papers, 4 papers with code
Extracting the Multiscale Causal Backbone of Brain Dynamics
The bulk of the research effort on brain connectivity revolves around statistical associations among brain regions, which do not directly relate to the causal mechanisms governing brain dynamics.
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales
We posit that machine learning will be the cornerstone of future collection, processing, and analysis of multimodal streams of data in animal communication studies, including bioacoustic, behavioral, biological, and environmental data.
On The Topological Expressive Power of Neural Networks
We propose a topological description of neural network expressive power.
Hypergraph reconstruction from network data
Pairwise representations nonetheless remain ubiquitous, because higher-order interactions are often not recorded explicitly in network data.
Simplex2Vec embeddings for community detection in simplicial complexes
Topological representations are rapidly becoming a popular way to capture and encode higher-order interactions in complex systems.
Simplicial models of social contagion
Complex networks have been successfully used to describe the spreading of a disease in populations of interacting individuals.
Physics and Society
Construction of and efficient sampling from the simplicial configuration model
Simplicial complexes are now a popular alternative to networks when it comes to describing the structure of complex systems, primarily because they encode multi-node interactions explicitly.
Physics and Society Statistics Theory Methodology Statistics Theory
On the predictability of infectious disease outbreaks
As a result, predicting when, where, and how far diseases will spread requires a complex systems approach to modeling.
Physics and Society Populations and Evolution
