Results 11 to 20 of about 5,161,693 (301)
Network Inference with the Lasso
Multivariate Behavioral Research, 2022 Calculating confidence intervals and p-values of edges in networks is useful to decide their presence or absence and it is a natural way to quantify uncertainty. Since Lasso estimation is often used to obtain edges in a network, and the underlying distribution of Lasso estimates is discontinuous and has probability one at zero when the estimate is zero,
Lourens Waldorp, Jonas Haslbeck
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Inference of a probabilistic Boolean network from a single observed temporal sequence [PDF]
, 2007 The inference of gene regulatory networks is a key issue for genomic signal processing. This paper addresses the inference of probabilistic Boolean networks (PBNs) from observed temporal sequences of network states.
Xiao, Y. +3 more
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Network neutrality inference [PDF]
ACM SIGCOMM Computer Communication Review, 2014 When can we reason about the neutrality of a network based on external observations? We prove conditions under which it is possible to (a) detect neutrality violations and (b) localize them to specific links, based on external observations. Our insight is that, when we make external observations from different vantage points, these will most likely be ...
Zhang Zhiyong +2 more
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Inferring cellular networks – a review [PDF]
BMC Bioinformatics, 2007 In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical ...
Florian Markowetz, Rainer Spang
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Inferring networks of diffusion and influence [PDF]
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, 2010 Information diffusion and virus propagation are fundamental processes taking place in networks. While it is often possible to directly observe when nodes become infected with a virus or publish the information, observing individual transmissions (who infects whom, or who influences whom) is typically very difficult.
Manuel Gomez-Rodriguez +2 more
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Trace complexity of network inference [PDF]
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013 25 pages, preliminary version appeared in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2013)
Bruno Abrahao +3 more
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Network Cluster‐Robust Inference [PDF]
Econometrica, 2021 Since network data commonly consists of observations from a single large network, researchers often partition the network into clusters in order to apply cluster‐robust inference methods. Existing such methods require clusters to be asymptotically independent. Under mild conditions, we prove that, for this requirement to hold for network‐dependent data,
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Causal network inference using biochemical kinetics [PDF]
, 2014 Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models.
Bayani, Nora +11 more
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Frontiers in Genetics, 2022 COVID-19 is a heterogeneous disease caused by SARS-CoV-2. Aside from infections of the lungs, the disease can spread throughout the body and damage many other tissues, leading to multiorgan failure in severe cases. The highly variable symptom severity is
Yue Hu +13 more
doaj +1 more source
Extending the functional equivalence of radial basis functionnetworks and fuzzy inference systems [PDF]
, 1996 We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference.
R. Murray-Smith +5 more
core +3 more sources