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The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights into the functional properties of the IB; • discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and • offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information–theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence.

Information technology industries --- information theory --- variational inference --- machine learning --- learnability --- information bottleneck --- representation learning --- conspicuous subset --- stochastic neural networks --- mutual information --- neural networks --- information --- bottleneck --- compression --- classification --- optimization --- classifier --- decision tree --- ensemble --- deep neural networks --- regularization methods --- information bottleneck principle --- deep networks --- semi-supervised classification --- latent space representation --- hand crafted priors --- learnable priors --- regularization --- deep learning --- information theory --- variational inference --- machine learning --- learnability --- information bottleneck --- representation learning --- conspicuous subset --- stochastic neural networks --- mutual information --- neural networks --- information --- bottleneck --- compression --- classification --- optimization --- classifier --- decision tree --- ensemble --- deep neural networks --- regularization methods --- information bottleneck principle --- deep networks --- semi-supervised classification --- latent space representation --- hand crafted priors --- learnable priors --- regularization --- deep learning

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The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights into the functional properties of the IB; • discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and • offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information–theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence.

information theory --- variational inference --- machine learning --- learnability --- information bottleneck --- representation learning --- conspicuous subset --- stochastic neural networks --- mutual information --- neural networks --- information --- bottleneck --- compression --- classification --- optimization --- classifier --- decision tree --- ensemble --- deep neural networks --- regularization methods --- information bottleneck principle --- deep networks --- semi-supervised classification --- latent space representation --- hand crafted priors --- learnable priors --- regularization --- deep learning

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Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine

Technology: general issues --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning

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Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine

Technology: general issues --- city interaction network --- evolution model --- preferential attachment --- WeChat --- maximum likelihood --- chimera states --- coupled map lattice --- nilpotent matrix --- community detection --- membrane algorithm --- self-organizing map network --- complex networks --- optimization --- structural balance --- minimum memory based sign adjustment --- social networks --- NW network --- convergence --- complex system simulation --- cloud computing architecture --- service-oriented modeling --- semantic search framework --- QoS-based service selection --- cascading failures --- network topology --- null models --- SciSci --- knowledge evolution --- machine learning --- bridging centrality --- disjoint nodes --- disjunct nodes --- node similarity --- overlapping nodes --- Bayesian networks --- entropy --- socio-ecological system --- complex network --- chaotic time series --- Gaussian mixture model --- maximum mean discrepancy --- angiogenesis --- network properties --- variational inference --- graph neural network --- variational autoencoder --- network embedding --- online social networks --- social media --- information spreading --- information diffusion --- cross-entropy --- cross-domain recommendation --- sentiment analysis --- latent sentiment review feature --- non-linear mapping --- dissimilarity spaces --- support vector machines --- kernel methods --- computational biology --- systems biology --- protein contact networks --- data mining --- overlapping communities --- modularity --- literary works --- genre classification --- stylistic attributes --- lemmatization --- renormalisation process --- network growth --- inverse preferential attachment --- language networks --- language development --- multilayer complex networks --- stability --- spreading control --- graph neural networks --- node classification --- active learning --- graph representation learning --- n/a

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The aim of this Printed Edition of Special Issue entitled "Recent Advancements in Radar Imaging and Sensing Technology” was to gather the latest research results in the area of modern radar technology using active and/or radar imaging sensing techniques in different applications, including both military use and a broad spectrum of civilian applications. As a result, the 19 papers that have been published highlighted a variety of topics related to modern radar imaging and microwave sensing technology. The sequence of articles included in the Printed Edition of Special Issue dealt with wide aspects of different applications of radar imaging and sensing technology in the area of topics including high-resolution radar imaging, novel Synthetic Apertura Radar (SAR) and Inverse SAR (ISAR) imaging techniques, passive radar imaging technology, modern civilian applications of using radar technology for sensing, multiply-input multiply-output (MIMO) SAR imaging, tomography imaging, among others.

Technology: general issues --- microwave staring correlated imaging (MSCI) --- gain–phase errors --- strip --- self-calibration --- distributed MIMO radar --- target localization --- double-sided bistatic range (BR) --- microwave staring correlated imaging --- unsteady aerostat platform --- motion parameter fitting --- position error --- radar imaging --- synthetic aperture radar --- compressed sensing --- sparse reconstruction --- regularization --- passive forward scattering radar --- chirp rate estimation --- passive radar --- forward scattering radar --- radar measurements --- time-frequency analysis --- bistatic synthetic aperture radar (SAR) --- hyperbolic approximation --- phase compensation --- modified omega-K --- ground-penetrating radar --- noise suppression --- singular value decomposition --- Hankel matrix --- window length optimization --- synthetic aperture radar (SAR) --- high resolution wide swath (HRWS) --- azimuth multichannel reconstruction --- phase center adaptation --- false targets suppression --- damped exponential (DE) model --- inverse synthetic aperture radar (ISAR) --- radar signatures --- state–space approach (SSA) --- sparse representation --- polarimetric --- SAR tomography --- MIMO radar --- noise radar --- radar signal processing techniques --- analogue correlation --- modern radar applications --- delay line --- high pulse repetition frequency (HPRF) --- random frequency hopping (RFH) --- hypersonic aircraft --- SAR --- Synthetic Aperture Radar --- ASIFT --- Despeckling Filter --- Navigation --- Structure from Motion --- Iterative Closest Point --- radar tomography --- compressive sensing --- bistatic radar --- parameter-refined orthogonal matching pursuit (PROMP) --- orthogonal matching pursuit (OMP) --- k-space tomography --- narrowband radar --- off-grid compressive sensing --- slow-time k-space --- spatial frequency --- Doppler radar tomography --- k-space augmentation --- high-resolution narrowband radar --- multiband processing --- bandwidth stitching --- multi-scale representation learning (MSRL) --- pyramid pooling module (PPM) --- compact depth-wise separable convolution (CSeConv) --- convolution auto-encoder (CAE) --- object classification --- CARABAS II --- ground scene prediction --- image stack --- multi-pass --- SAR images --- moving targets --- inverse SAR (ISAR) --- motion compensation --- hybrid SAR/ISAR --- improved rank-one phase estimation (IROPE) --- Gaofen-3 (GF-3) --- assive radar --- time-frequency reassignment --- microwave staring correlated imaging (MSCI) --- gain–phase errors --- strip --- self-calibration --- distributed MIMO radar --- target localization --- double-sided bistatic range (BR) --- microwave staring correlated imaging --- unsteady aerostat platform --- motion parameter fitting --- position error --- radar imaging --- synthetic aperture radar --- compressed sensing --- sparse reconstruction --- regularization --- passive forward scattering radar --- chirp rate estimation --- passive radar --- forward scattering radar --- radar measurements --- time-frequency analysis --- bistatic synthetic aperture radar (SAR) --- hyperbolic approximation --- phase compensation --- modified omega-K --- ground-penetrating radar --- noise suppression --- singular value decomposition --- Hankel matrix --- window length optimization --- synthetic aperture radar (SAR) --- high resolution wide swath (HRWS) --- azimuth multichannel reconstruction --- phase center adaptation --- false targets suppression --- damped exponential (DE) model --- inverse synthetic aperture radar (ISAR) --- radar signatures --- state–space approach (SSA) --- sparse representation --- polarimetric --- SAR tomography --- MIMO radar --- noise radar --- radar signal processing techniques --- analogue correlation --- modern radar applications --- delay line --- high pulse repetition frequency (HPRF) --- random frequency hopping (RFH) --- hypersonic aircraft --- SAR --- Synthetic Aperture Radar --- ASIFT --- Despeckling Filter --- Navigation --- Structure from Motion --- Iterative Closest Point --- radar tomography --- compressive sensing --- bistatic radar --- parameter-refined orthogonal matching pursuit (PROMP) --- orthogonal matching pursuit (OMP) --- k-space tomography --- narrowband radar --- off-grid compressive sensing --- slow-time k-space --- spatial frequency --- Doppler radar tomography --- k-space augmentation --- high-resolution narrowband radar --- multiband processing --- bandwidth stitching --- multi-scale representation learning (MSRL) --- pyramid pooling module (PPM) --- compact depth-wise separable convolution (CSeConv) --- convolution auto-encoder (CAE) --- object classification --- CARABAS II --- ground scene prediction --- image stack --- multi-pass --- SAR images --- moving targets --- inverse SAR (ISAR) --- motion compensation --- hybrid SAR/ISAR --- improved rank-one phase estimation (IROPE) --- Gaofen-3 (GF-3) --- assive radar --- time-frequency reassignment