Information diffusion in social media shapes public opinion and collective behavior, making its modeling and simulation an important research problem. Existing studies have investigated information di...
The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support the...
Bipartite graphs serve as a natural model for representing relationships between two different types of entities. When analyzing bipartite graphs, butterfly counting is a fundamental research problem ...
Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a bipartite dependency network, a graph with two t...
The Gaussian mixture model is widely used in unsupervised learning, owing to its simplicity and interpretability. However, a fundamental limitation of the classical Gaussian mixture model is that it f...
The cross-lagged panel model (CLPM) has been widely used, particularly in psychology, to infer longitudinal relations among variables. At the same time, controlling for between-person heterogeneity an...
Data-driven causal relationship identification is pertinent to advancing understanding of complex systems both within and beyond science. Bayesian networks offer a probabilistic method for modelling g...
Generating novel, biologically plausible three-dimensional morphological structures is a fundamental challenge in computational evolutionary biology, hampered by extreme data scarcity and the requirem...
The Hyperspace Analogue to Language (HAL) model relies on global word co-occurrence matrices to construct distributional semantic representations. While these representations capture lexical relations...
Generating motion-controlled videos--where user-specified actions drive physically plausible scene dynamics under freely chosen viewpoints--demands two capabilities: (1) disentangled motion control, a...
We introduce cyclinbayes, an open-source R package for discovering linear causal relationships with both acyclic and cyclic structures. The package employs scalable Bayesian approaches with spike-and-...
For a phenomenon $\pmb{f}$ that is a function of $\mathit{n}$ factors, defined on a finite abelian group $\mathcal{G}$, we derive its population statistics solely from its Fourier transform $\hat{\pmb...
This paper develops a unified framework for measuring concentration in weighted systems embedded in networks of interactions. While traditional indices such as the Herfindahl-Hirschman Index capture d...
Systematic investment strategies are exposed to a subtle but pervasive vulnerability: the progressive erosion of their effectiveness as market regimes change. Traditional risk measures, designed to ca...
Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes through intermediate structures such as layouts and scene graphs, yet evaluation still relies on LLM ...
The deep-sea shrimp, Aristeus alcocki Ramadan, 1938, is an economically valuable species belonging to the family Aristeidae under the superfamily Penaeoidea. In this study, we report the complete mito...
Large language models (LLMs) are increasingly used to answer natural-language questions over structured data. However, when a table contains familiar real-world facts, it is unclear whether the model ...
People of the Jomon period in Japan led a hunter-gatherer lifestyle and actively engaged in fishing in coastal areas. On the Atsumi Peninsula, which is located in the southern part of Aichi Prefecture...
Symbiotic relationships are ubiquitous across nature and play key roles in the maintenance of biodiversity and ecosystem function. The Myzostomida are an enigmatic clade of marine annelids that live a...
This study provides data on concentrations of polycyclic aromatic hydrocarbons (PAHs) in Mediterranean mussels (Mytilus galloprovincialis), from the eastern Black Sea (Sochi, Russia). At all stations ...
🌊
