134 citations · 291 across the 18 of their papers we have counts for
20 papers
Topological measures in weighted hypergraphs
Ekaterina Vasilyeva, Liubov Tupikina, Daniil Musatov +3
Higher-order interactions introduce an additional structural dimension to complex networks, requiring consistent generalizations of classical topological measures. In hypergraphs,…
Thinking Before Constraining: A Unified Decoding Framework for Large Language Models
Ngoc Trinh Hung Nguyen, Alonso Silva, Laith Zumot +3
Natural generation allows Large Language Models (LLMs) to produce free-form responses with rich reasoning, yet the lack of structure makes outputs difficult to verify. Conversely,…
Iterative Ricci-Foster Curvature Flow with GMM-Based Edge Pruning: A Novel Approach to Community Detection
Arsenii Onuchin, Konstantin Sorokin, Maxim Beketov +1
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on R…
Two-dimensional Taxonomy for N-ary Knowledge Representation Learning Methods
Xiaohua Lu, Liubov Tupikina, Mehwish Alam
Real-world knowledge can take various forms, including structured, semi-structured, and unstructured data. Among these, Knowledge Graphs (KGs) are structured representations that i…
Dissecting embedding method: learning higher-order structures from data
Liubov Tupikina, Kathuria Hritika
Active area of research in AI is the theory of manifold learning and finding lower-dimensional manifold representation on how we can learn geometry from data for providing better q…
Transport collapse in dynamically evolving networks
Geoffroy Berthelot, Liubov Tupikina, Min-Yeong Kang +2
Transport in complex networks can describe a variety of natural and human-engineered processes including biological, societal and technological ones. However, how the properties of…
Charting mobility patterns in the scientific knowledge landscape
Chakresh Kumar Singh, Liubov Tupikina, Fabrice Lécuyer +2
From small steps to great leaps, metaphors of spatial mobility abound to describe discovery processes. Here, we ground these ideas in formal terms by systematically studying scient…
iNaturalist citizen science community during City Nature Challenge: new computational approach for analysis of user activity
Liubov Tupikina, Frank Schlosser, Vadim Voskresenskii +6
Analysing patterns of engagement among citizen science participants can provide important insights into the organisation and practice of individual citizen science projects. In par…
Quantifying the rise and fall of scientific fields
Chakresh Singh, Emma Barme, Robert Ward +2
Science advances by pushing the boundaries of the adjacent possible. While the global scientific enterprise grows at an exponential pace, at the mesoscopic level the exploration an…
Modelling railway delay propagation as diffusion-like spreading
Mark M. Dekker, Alexey N. Medvedev, Jan Rombouts +2
Railway systems form an important means of transport across the world. However, congestions or disruptions may significantly decrease these systems' efficiencies, making predicting…
Pseudo-Darwinian evolution of physical flows in complex networks
Geoffroy Berthelot, Liubov Tupikina, Min-Yeong Kang +2
The evolution of complex transport networks is investigated under three strategies of link removal: random, intentional attack and "Pseudo-Darwinian" strategy. At each evolution st…
Continuous limits of Heterogeneous Continuous Time Random Walk model
Liubov Tupikina
Continuous time random Walk model has been versatile analytical formalism for studying and modeling diffusion processes in heterogeneous structures, such as disordered or porous me…
Morphological organization of point-to-point transport in complex networks
Min-Yeong Kang, Geoffroy Berthelot, Liubov Tupikina +4
We investigate the structural organization of the point-to-point electric, diffusive or hydraulic transport in complex scale-free networks. The random choice of two nodes, a source…
Structural and temporal heterogeneities on networks
Liubov Tupikina, Denis S. Grebenkov
A heterogeneous continuous time random walk is an analytical formalism for studying and modeling diffusion processes in heterogeneous structures on microscopic and macroscopic scal…
Epidemic extinction in networks: Insights from the 12,110 smallest graphs
Petter Holme, Liubov Tupikina
We investigate the expected time to extinction in the susceptible-infectious-susceptible (SIS) model of disease spreading. Rather than using stochastic simulations, or asymptotic c…
Heterogeneous continuous time random walks
Denis S. Grebenkov, Liubov Tupikina
We introduce a heterogeneous continuous time random walk (HCTRW) model as a versatile analytical formalism for studying and modeling diffusion processes in heterogeneous structures…
Dynamics on networks. Case of Heterogeneous Opinion Status Model
Liubov Tupikina
Here we developed a new conceptual, stochastic Heterogeneous Opinion-Status model (HOpS model), which is adaptive network model. The HOpS model admits to identify the main attribut…
Correlation networks from flows. The case of forced and time-dependent advection-diffusion dynamics
Liubov Tupikina, Nora Molkenthin, Cristóbal López +3
Complex network theory provides an elegant and powerful framework to statistically investigate different types of systems such as society, brain or the structure of local and long-…
Edge anisotropy and the geometric perspective on flow networks
Nora Molkenthin, Hannes Kutza, Liubov Tupikina +5
Spatial networks have recently attracted great interest in various fields of research. While the traditional network-theoretic viewpoint is commonly restricted to their topological…
Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package
Jonathan F. Donges, Jobst Heitzig, Boyan Beronov +9
We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of dat…