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Alice Patania

Researcher at Indiana University

Publications -  21
Citations -  1258

Alice Patania is an academic researcher from Indiana University. The author has contributed to research in topics: Topological data analysis & Computer science. The author has an hindex of 7, co-authored 18 publications receiving 605 citations. Previous affiliations of Alice Patania include Institute for Scientific Interchange & Polytechnic University of Turin.

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Journal ArticleDOI

Networks beyond pairwise interactions: Structure and dynamics

Federico Battiston, +8 more
- 25 Aug 2020 - 
TL;DR: A complete overview of the emerging field of networks beyond pairwise interactions, and focuses on novel emergent phenomena characterizing landmark dynamical processes, such as diffusion, spreading, synchronization and games, when extended beyond Pairwise interactions.
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The shape of collaborations

Alice Patania, +4 more
- 24 Aug 2017 - 
TL;DR: It is shown that it is natural to extend the concept of triadic closure to simplicial complexes and show the presence of strong simplicial closure, and that homological cycles are an important part of the underlying community linking structure.
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Topological analysis of data

Alice Patania, +4 more
- 01 Dec 2017 - 
TL;DR: The TDA paradigm is presented and some applications are presented, in order to highlight its relevance to the data science community.
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Construction of and efficient sampling from the simplicial configuration model.

Jean-Gabriel Young, +5 more
- 22 Sep 2017 - 
TL;DR: This work proposes a natural candidate, the simplicial configuration model, and demonstrates its usefulness in a short case study by investigating the topology of three real systems and their randomized counterparts (using their Betti numbers).
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Navigating features: a topologically informed chart of electromyographic features space.

Angkoon Phinyomark, +5 more
- 01 Dec 2017 - 
TL;DR: This feature chart is used to identify functional groups among 58 state-of-the-art EMG features, and to show that they generalize across three different forearm EMG datasets obtained from able-bodied subjects during hand and finger contractions.