activity
20082022
most citedCausality-Driven Slow-Down and Speed-Up of Diffusion in Non-Markovian Temporal Networks

314 citations · 1.5k across the 25 of their papers we have counts for

collaborators
Showing 2015 · physics.soc-phShow all

7 papers · 2 filters

physics.soc-ph2015★ 2 cited

The network structure of city-firm relations

Antonios Garas, Celine Rozenblat, Frank Schweitzer

How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and econ…

physics.soc-ph2015

The spatial component of R&D networks

Tobias Scholl, Antonios Garas, Frank Schweitzer

We study the role of geography in R&D networks by means of a quantitative, micro-geographic approach. Using a large database that covers international R&D collaborations from 1984…

physics.soc-ph2015★ 69 cited

Higher-Order Aggregate Networks in the Analysis of Temporal Networks: Path structures and centralities

Ingo Scholtes, Nicolas Wider, Antonios Garas

Recent research on temporal networks has highlighted the limitations of a static network perspective for our understanding of complex systems with dynamic topologies. In particular…

physics.soc-ph2015★ 7 cited

An ensemble perspective on multi-layer networks

Nicolas Wider, Antonios Garas, Ingo Scholtes +1

We study properties of multi-layered, interconnected networks from an ensemble perspective, i.e. we analyze ensembles of multi-layer networks that share similar aggregate character…

physics.soc-ph2015★ 44 cited

Systemic risk in multiplex networks with asymmetric coupling and threshold feedback

Rebekka Burkholz, Matt V. Leduc, Antonios Garas +1

We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process appr…

physics.soc-ph2015★ 53 cited

Value of peripheral nodes in controlling multilayer networks

Yan Zhang, Antonios Garas, Frank Schweitzer

We analyze the controllability of a two-layer network, where driver nodes can be chosen randomly only from one layer. Each layer contains a scale-free network with directed links a…