Results 281 to 290 of about 166,926 (313)
Some of the next articles are maybe not open access.
2014
Network graphs are constructed in all sorts of ways and to varying levels of completeness. In some settings, there is little if any uncertainty in assessing whether or not an edge exists between two vertices and we can exhaustively assess incidence between vertex pairs.
Eric D. Kolaczyk, Gábor Csárdi
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Network graphs are constructed in all sorts of ways and to varying levels of completeness. In some settings, there is little if any uncertainty in assessing whether or not an edge exists between two vertices and we can exhaustively assess incidence between vertex pairs.
Eric D. Kolaczyk, Gábor Csárdi
openaire +1 more source
BENIN: Biologically enhanced network inference
Journal of Bioinformatics and Computational Biology, 2020Gene regulatory network inference is one of the central problems in computational biology. We need models that integrate the variety of data available in order to use their complementarity information to overcome the issues of noisy and limited data.
Stephanie Kamgnia, Wonkap +1 more
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Motif-aware diffusion network inference
International Journal of Data Science and Analytics, 2018Characterizing and understanding information diffusion over social networks play an important role in various real-world applications. In many scenarios, however, only the states of nodes can be observed while the underlying diffusion networks are unknown.
Qi Tan, Yang Liu, Jiming Liu
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Bayonet: probabilistic inference for networks
Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018Network operators often need to ensure that important probabilistic properties are met, such as that the probability of network congestion is below a certain threshold. Ensuring such properties is challenging and requires both a suitable language for probabilistic networks and an automated procedure for answering probabilistic inference queries.
Gehr, Timon +5 more
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2018
Background: A reliable inference of networks from data is of key interest in the Neurosciences. Several methods have been suggested in the literature to reliably determine links in a network. To decide about the presence of links, these techniques rely on statistical inference, typically controlling the number of false positives, paying little ...
Cecchini, Gloria (Dr.) +3 more
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Background: A reliable inference of networks from data is of key interest in the Neurosciences. Several methods have been suggested in the literature to reliably determine links in a network. To decide about the presence of links, these techniques rely on statistical inference, typically controlling the number of false positives, paying little ...
Cecchini, Gloria (Dr.) +3 more
openaire +1 more source
Inferring Ancestral Protein Interaction Networks
2008With the recent sequencing of numerous complete genomes and the advent of high throughput technologies (e.g., yeast two-hybrid assays or tandem-affinity purification experiments), it is now possible to estimate the ancestral form of protein interaction networks.
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Generative replay underlies compositional inference in the hippocampal-prefrontal circuit
Cell, 2023Philipp Schwartenbeck
exaly
Causal inference for time series
Nature Reviews Earth & Environment, 2023Jakob Runge, Gherardo Varando
exaly