What are higher-order networks?
Network-based modeling of complex systems and data using the language of graphs has
become an essential topic across a range of different disciplines. Arguably, this graph-based …
become an essential topic across a range of different disciplines. Arguably, this graph-based …
Topological data analysis
L Wasserman - Annual Review of Statistics and Its Application, 2018 - annualreviews.org
Topological data analysis (TDA) can broadly be described as a collection of data analysis
methods that find structure in data. These methods include clustering, manifold estimation …
methods that find structure in data. These methods include clustering, manifold estimation …
Learnable latent embeddings for joint behavioural and neural analysis
Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our
ability to record large neural and behavioural data increases, there is growing interest in …
ability to record large neural and behavioural data increases, there is growing interest in …
Toroidal topology of population activity in grid cells
The medial entorhinal cortex is part of a neural system for mapping the position of an
individual within a physical environment. Grid cells, a key component of this system, fire in a …
individual within a physical environment. Grid cells, a key component of this system, fire in a …
[PDF][PDF] A roadmap for the computation of persistent homology
Persistent homology (PH) is a method used in topological data analysis (TDA) to study
qualitative features of data that persist across multiple scales. It is robust to perturbations of …
qualitative features of data that persist across multiple scales. It is robust to perturbations of …
The why, how, and when of representations for complex systems
Complex systems, composed at the most basic level of units and their interactions, describe
phenomena in a wide variety of domains, from neuroscience to computer science and …
phenomena in a wide variety of domains, from neuroscience to computer science and …
Two's company, three (or more) is a simplex: Algebraic-topological tools for understanding higher-order structure in neural data
The language of graph theory, or network science, has proven to be an exceptional tool for
addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a …
addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a …
The importance of the whole: topological data analysis for the network neuroscientist
Data analysis techniques from network science have fundamentally improved our
understanding of neural systems and the complex behaviors that they support. Yet the …
understanding of neural systems and the complex behaviors that they support. Yet the …
Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features
T Qaiser, YW Tsang, D Taniyama, N Sakamoto… - Medical image …, 2019 - Elsevier
Tumor segmentation in whole-slide images of histology slides is an important step towards
computer-assisted diagnosis. In this work, we propose a tumor segmentation framework …
computer-assisted diagnosis. In this work, we propose a tumor segmentation framework …
[图书][B] Topological data analysis for genomics and evolution: topology in biology
R Rabadán, AJ Blumberg - 2019 - books.google.com
Biology has entered the age of Big Data. The technical revolution has transformed the field,
and extracting meaningful information from large biological data sets is now a central …
and extracting meaningful information from large biological data sets is now a central …