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.
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Showing 1 to 20 of 22 for “"Dynamic graphs"”.
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Estimating Reachability Set Sizes in Dynamic Graphs
Graphs are a commonly used abstraction for diverse kinds of interactions, e.g., on Twitter and Facebook. Different kinds of topological properties of such graphs are computed for gaining insights into their structure. Computing properties of large real networks is computationally very challenging. …
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Implementing Quantum Gates With Length-3 Dynamic Graphs
… equal to the adjacency matrix of a sequence of graphs, called a dynamic graph, continuous-time quantum walks have been shown to implement quantum gates, including the T gate, Hadamard gate, and the Controlled{NOT gate. Since these gates make up a universal set of quantum gates, they can …
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Optimizing the Analysis of Electroencephalographic Data by Dynamic Graphs
… in this area has so far been mostly on static graphs, the complex and dynamic nature of the brain’s underlying mechanism has initiated the usage of dynamic graphs, providing groundwork for time sensi- tive and finer investigations. Studying the topological reconfiguration of these dynamic …
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Exploring Neuroimaging-Specific Deep Learning Biases: Uncertainty, Dynamic Graphs, and Communities
The human brain is a complex dynamical system composed of numerous interacting regions. It has long been a subject of immense interest for neuroscientists seeking to understand brain function. Recent technological advancements have introduced non-invasive functional neuroimaging techniques, …
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Nonpreemptive Run-Time Scheduling Issues on a Multitasked, Multiprogrammed Multiprocessor With Dependencies, Bidimensional Tasks, Folding, and Dynamic Graphs
… The model consists of directed, acyclic graphs, generated from serial FORTRAN benchmark programs by the parallel compiler Parafrase. A multitasked, multiprogrammed environment is created. Dependencies are generated by the compiler. Tasks are bidimensional, i.e., they may specify both time …
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Supporting Dynamic Queries and Annotations Over Data Graphs
… such as those derived from social networks and dynamic distributed systems, we often need to associate metadata with whole subgraphs of data. In particular, provenance and trustworthinessare examples of metadata that can be associated to entire sugbraphs. To the extent of our knowledge, however, …
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Converting PyTorch Models to StreamIt Pipelines
… learning libraries such as PyTorch produce dynamic computation graphs in order to represent the forward pass of the model. PyTorch allows conversion of these dynamic graphs into static ones through just-in-time (JIT) compilation. These graphs can then be optimized further by the compiler. We …
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A Web Based Application for Model Creation and Output Visualization with the NCS Brain Simulator
… as well as visualizing outputs in realtime as dynamic graphs. It also has the ability to view constructed models in 3D. The web interface has many features to work with NCS directly, including the ability to launch simulations, save working models to a database, or export models as JSON files …
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Dynamic reconfigurable battery systems via graph-based deep reinforcement learning
… management, making it difficult to respond to dynamic cell imbalance and thereby reducing overall battery operating time. To address these limitations, reconfigurable battery designs have been proposed where the interconnection topology among cells can be adjusted in real time to reflect …
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Object-centric temporal navigation for dynamic information visualizations.
… can be designed for different types of dynamic visualizations, we created two techniques: DimpVis, for exploring changing visual variables in different information visualizations, and Glidgets, for exploring topological changes in dynamic graphs. Both techniques enable intuitive …
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Image alignment and dynamic graph analytics : two case studies of how managing data movement can make (parallel) code run fast
… cluster. The second case study explores dynamic graph analytics, where I describe the design of a new data structure for storing dynamic graphs that matches the performance of standard, static formats and enables high performance, dynamic operations achieving millions of updates per …
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Educational Technology and Teacher Perceptions: How does the technology fare in the wild?
… of change and proportionality, utilizing dynamic graphs and animated "worlds". SimCalc is the package of MathWorlds software plus curriculum and teacher professional development, and has a history of significant success in single classroom studies. According to Simonsen and Kensing (1998), …
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Graph neural network approaches and real-time unsupervised learning for anomaly detection in vehicular networks
… vehicle interactions are modeled as dynamic graphs and evaluated using six Graph Neural Network (GNN) architectures: Graph Convolutional Network (GCN), Graph Attention Network (GAT), GraphSAGE, Temporal GCN (T-GCN), Gated Convolutional LSTM (GConvLSTM), and Gated Convolutional GRU …
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Low latency queries on big graph data
… these goals is impossible for extremely dense graphs. The central theme of this dissertation is to show that these goals can, in fact, be achieved by exploiting {\em graph sparsity}, a property almost always encountered in big graph data. This dissertation formally establishes a separation …
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Dynamic Large-Scale Graph Processing over Data Streams with Community Detection as a Case Study
Processing large graphs provides invaluable insights for the industry and research alike. The applications range from e-commerce, web, and social networking to analyzing gene expressions and cellular signaling. While numerous graph processing solutions have been developed with the capability to …
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Graph-based Approach for Anomaly Detection in Video Surveillance
… The first part introduces a method based on dynamic graphs to represent motion and semantic information present in the scene. This method utilizes hand-crafted features as well as graphs properties to extract useful information from video sequences. The second part presents an offline …
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Distributional and relational inductive biases for graph representation learning in biomedicine
… functions of biomolecular entities using graphs and networks. This dissertation considers how we may use the inductive biases within recent graph representation learning methods to leverage these structures and incorporate biologically relevant relational priors into machine learning …
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Encoding parameter and structural efficiency in deep learning
… multi-armed bandits. The method can dynamically, that is during training, identify a high-performing compact subnetwork within an overparameterized model while adhering to a predefined memory utilization budget. This is achieved by associating a saliency metric with each neuron, which …
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Mine the node association: Dig into the essence of graphs
… with other types of data, the essence of graphs large lies in node association, which represents unique, informative and important relation between nodes. Recently, mining the node association has attracted remarkable attentions in many high-impact domains, such as academic collaboration, …
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Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion
… discovering and blocking bottleneck edges in the graphs, we first prove that deriving an optimal defensive policy is #P-hard. We design a kernelization technique that reduces the active directory graph to a much smaller condensed graph. We propose an effective edge-blocking defensive policy by …
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