arXiv subjects

Pavel Sanda

Publications and source records attributed to Pavel Sanda.

3 recordsLinked to original sources

arXiv2026

Making the complete OpenAIRE citation graph easily accessible through compact data representation

The OpenAIRE graph contains a large citation graph dataset, with over 200 million publications and over 2 billion citations. The current graph is available as a dump with metadata which, when uncompressed, totals $\sim$2.5 TB. This makes it hard to process on conventional computers. To make this network more accessible for the community, we provide a processed OpenAIRE graph which is downscaled to 16 GB RAM, while preserving the full graph structure. Apart from this we offer the processed data in a very simple format, which allows for further straightforward manipulation. We also provide (1) a Python pipeline, which can be used to process the next releases of the OpenAIRE graph, and (2) a larger version of the dataset including more publication fields such as, the title, list of authors.

cs.SI↗

arXiv2024

Higher order definition of causality by optimally conditioned transfer entropy

The description of the dynamics of complex systems, in particular the capture of the interaction structure and causal relationships between elements of the system, is one of the central questions of interdisciplinary research. While the characterization of pairwise causal interactions is a relatively ripe field with established theoretical concepts and the current focus is on technical issues of their efficient estimation, it turns out that the standard concepts such as Granger causality or transfer entropy may not faithfully reflect possible synergies or interactions of higher orders, phenomena highly relevant for many real-world complex systems. In this paper, we propose a generalization and refinement of the information-theoretic approach to causal inference, enabling the description of truly multivariate, rather than multiple pairwise, causal interactions, and moving thus from causal networks to causal hypernetworks. In particular, while keeping the ability to control for mediating variables or common causes, in case of purely synergetic interactions such as the exclusive disjunction, it ascribes the causal role to the multivariate causal set but \emph{not} to individual inputs, distinguishing it thus from the case of e.g. two additive univariate causes. We demonstrate this concept by application to illustrative theoretical examples as well as a biophysically realistic simulation of biological neuronal dynamics recently reported to employ synergetic computations.

stat.ML↗

arXiv2020

On the precision of neural computation with interaural time differences in the medial superior olive

Incoming sound is in cochlea and auditory nerve encoded into spike trains. At the third neuron of the auditory pathway, spike trains of the left and right sides are processed in brainstem nuclei to yield sound localization information. Two different localization encoding mechanisms are employed in two centers for low and high sound frequencies in the brainstem. The centers are superior olivary nuclei, medial and lateral. This paper contains analytical estimates of parameters needed in description of auditory coding in sound localization neural circuit. Our model spike trains are based on electro-physiological recordings. We arrive to best estimates for neuronal signaling with the use of just noticeable difference of the ideal observer. We describe spike timing jitter and its role in the spike train processing. All parameters are accompanied with detailed estimates of their values and variability. Intervals bounding all the parameter from lower and higher values are discussed.

q-bio.NC↗