Information decomposition and the informational architecture of the brain
To explain how the brain orchestrates information-processing for cognition, we must
understand information itself. Importantly, information is not a monolithic entity. Information …
understand information itself. Importantly, information is not a monolithic entity. Information …
A review of entropy measures for uncertainty quantification of stochastic processes
Entropy is originally introduced to explain the inclination of intensity of heat, pressure, and
density to gradually disappear over time. Based on the concept of entropy, the Second Law …
density to gradually disappear over time. Based on the concept of entropy, the Second Law …
[HTML][HTML] The molecular signatures database hallmark gene set collection
Summary The Molecular Signatures Database (MSigDB) is one of the most widely used and
comprehensive databases of gene sets for performing gene set enrichment analysis. Since …
comprehensive databases of gene sets for performing gene set enrichment analysis. Since …
Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies
Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel
pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell …
pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell …
[KSIĄŻKA][B] Applied smoothing techniques for data analysis: the kernel approach with S-Plus illustrations
AW Bowman, A Azzalini - 1997 - books.google.com
The book describes the use of smoothing techniques in statistics, including both density
estimation and nonparametric regression. Considerable advances in research in this area …
estimation and nonparametric regression. Considerable advances in research in this area …
Estimating divergence functionals and the likelihood ratio by convex risk minimization
We develop and analyze M-estimation methods for divergence functionals and the
likelihood ratios of two probability distributions. Our method is based on a nonasymptotic …
likelihood ratios of two probability distributions. Our method is based on a nonasymptotic …
Finding the number of clusters in a dataset: An information-theoretic approach
One of the most difficult problems in cluster analysis is identifying the number of groups in a
dataset. Most previously suggested approaches to this problem are either somewhat ad hoc …
dataset. Most previously suggested approaches to this problem are either somewhat ad hoc …
[KSIĄŻKA][B] Statistical inference based on divergence measures
L Pardo - 2018 - taylorfrancis.com
The idea of using functionals of Information Theory, such as entropies or divergences, in
statistical inference is not new. However, in spite of the fact that divergence statistics have …
statistical inference is not new. However, in spite of the fact that divergence statistics have …
[KSIĄŻKA][B] Multivariate t-distributions and their applications
S Kotz, S Nadarajah - 2004 - books.google.com
Almost all the results available in the literature on multivariate t-distributions published in the
last 50 years are now collected together in this comprehensive reference. Because these …
last 50 years are now collected together in this comprehensive reference. Because these …
Earthquake damage assessment of buildings using VHR optical and SAR imagery
D Brunner, G Lemoine… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
Rapid damage assessment after natural disasters (eg, earthquakes) and violent conflicts
(eg, war-related destruction) is crucial for initiating effective emergency response actions …
(eg, war-related destruction) is crucial for initiating effective emergency response actions …