Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 41 for “"Network Representation"”.
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Network representation for combat models
A general network methodology for combat processes is presented in this thesis for use in the Airland Research Model. Specifically, two processes are developed in detail: the underlying transportation system and the command and control connectivity structure. Attributes necessary to support …
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Network Representation Learning with Attributes and Heterogeneity
Network Representation Learning (NRL) aims at learning a low-dimensional latent representation of nodes in a graph while preserving the graph information. The learned representation enables to easily and efficiently perform various machine learning tasks. Graphs are often associated with diverse …
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Evolving Network Representation Learning Based on Random Walks
Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that can be utilized to perform highly accurate and scalable …
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Modeling the Geometry of Neural Network Representation Spaces
Neural networks automate the process of representing objects and their relations on a computer, including everything from household items to molecules. New representations are obtained by transforming different instances into a shared representation space, where variations in data can be measured …
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Graph-theoretical consideration in the design of complex engineering systems for robustness and scalability
… to various engineering problems susceptible to network representation, including biological systems, telecommunication networks, transportation routes, and space exploration systems.
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Replicative network structures : theoretical definitions and analytical applications
… with the theory of musical transformations, network analysis stands out because of its broad applicability, demonstrated by the diverse examples presented in David Lewin’s seminal work Musical Form and Transformation and related articles by Lewin, Klumpenhouwer, Gollin, and others. While …
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An integrative and systems biology approach to interpreting, prioritizing, and analyzing the genetics of complex disorders.
… cocaine, nicotine, and opium, through exploiting network representation learning. A method for generating high-fidelity functional networks is outlined, and further, it is used for the quantification of genetic distances between classes of SUDs and cardiovascular disease. Multi-omics and …
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Information exchange between medical databases through automated identification of concept equivalence
… information exchange. MEDIATE employs a semantic network representation to model underlying native databases and to serve as an interface for database queries. This representation generates a semantic context for data concepts that can subsequently be exploited to perform automated concept …
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Setting location priors using beamforming improves model comparison in MEG-DCM
Modelling neuronal interactions using a directed network can be used to provide insight into the activity of the brain during experimental tasks. Magnetoencephalography (MEG) allows for the observation of the fast neuronal dynamics necessary to characterize the activity of sources and their …
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Interpretable Network Representations
<p>Networks (or interchangeably graphs) have been ubiquitous across the globe and within science and engineering: social networks, collaboration networks, protein-protein interaction networks, infrastructure networks, among many others. Machine learning on graphs, especially network representation …
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Nuclear and Chiral transition using the strong coupling expansion of Lattice QCD
… problem. To address this, we utilize the dual representation of lattice QCD obtained via the strong coupling expansion. The nuclear transition is studied in the strong coupling limit for large quark masses, and the necessary algorithmic developments for this regime are presented. Using the dual …
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Expressivity and Structure in Networks: Ising Models, Random Graphs, and Neural Networks.
Networks are used ubiquitously to model global phenomena which emerge due to interactions between multiple agents and are among the objects of fundamental interest in machine learning. The purpose of this dissertation is to understand expressivity and structure in various network models. The basic …
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Modeling wireless acoustic power transmission systems
… be discussed. Then an ABCD-parameter, two-port network representation is derived for a system compromising a piezoelectric transducer and a solid barrier. Such representations can be also be expressed in lumped-element circuits, which can be useful in designing the electrical end of the power …
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The planning and analysis implications of automated data collection systems : rail transit OD matrix inference and path choice modeling examples
… based on the inferred OD matrix and the transit network attributes. This study is based on two data sources: the rail trip OD matrix inferred in the first case study and the attributes of alternative paths calculated from a network representation in Trans CAD. This study demonstrates that a …
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Investigating Different Image Representations for Image Retrieval
… full images, image retrieval systems use image representations to allow the searching to happen faster while maintaining the image information to retrieve the correct image. The MIT Data Systems Group (DSG) created Seesaw, a system for interactive ad-hoc searches in image data sets with no …
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Lot streaming and batch scheduling: splitting and grouping jobs to improve production efficiency
… of resources and customer satisfaction. We use a network representation and critical path approach to analyse the lot streaming problem of finding optimal sublot sizes and a job sequence in a two-machine flow shop with transportation and setup times. We introduce a model where the number of …
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Value centric approach to target system modularization using multi-attribute tradespace exploration and network measures of component modularity
… Exploration, Multi-Epoch Analysis, and network measures of component modularity to identify components which are most likely to need to change as well as the components ability to make a modularity change. It is found that the tools utilized can be successfully linked to provide early …
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Simulation and optimization tools to study design principles of biological networks
… diagrams for a number of important biological networks. However, the design principles governing the construction and operation of these networks remain mostly unknown. To discover design principles in these networks, we investigated and developed a set of computational tools described below. …
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A Window to the Mind: Validation of a New Method to Measure Thought Dynamics Using Brain Network Meta-State Transitions
… during movie-viewing and at rest. I began with a representation of brain activity at each timepoint as the set of activations across 15 networks, and used new methods to embed this high-dimensional network representation onto a two-dimensional space of possible network configurations (network …
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Tensor Methods for Signal Reconstruction and Network Embedding
… signals? What is a concise and informative representation of entities in multi-dimensional networks? How do we develop efficient lightweight algorithms that handle very large data? These are important questions that have risen on the top of the scientific and engineering agenda of ML and SP …
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