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Thèses sur le sujet « Heterogeneous neural networks »

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Publié le 6 septembre 2023

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1

Belanche, Muñoz Lluís A. (Lluís Antoni). "Heterogeneous neural networks: theory and applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6660.

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Aquest treball presenta una classe de funcions que serveixen de models neuronals generalitzats per ser usats en xarxes neuronals artificials. Es defineixen com una mesura de similitud que actúa com una definició flexible de neurona vista com un reconeixedor de patrons. <br/>La similitud proporciona una marc conceptual i serveix de cobertura unificadora de molts models neuronals de la literatura i d'exploració de noves instàncies de models de neurona.<br/> <br/>La visió basada en similitud porta amb naturalitat a integrar informació heterogènia, com ara quantitats contínues i discretes (nomina

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Belanche, Muñoz Lluis. "Heterogeneous neural networks: theory and applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6660.

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Aquest treball presenta una classe de funcions que serveixen de models neuronals generalitzats per ser usats en xarxes neuronals artificials. Es defineixen com una mesura de similitud que actúa com una definició flexible de neurona vista com un reconeixedor de patrons. La similitud proporciona una marc conceptual i serveix de cobertura unificadora de molts models neuronals de la literatura i d'exploració de noves instàncies de models de neurona. La visió basada en similitud porta amb naturalitat a integrar informació heterogènia, com ara quantitats contínues i discretes (nominals i ordinals),

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Cabana, Tanguy. "Large deviations for the dynamics of heterogeneous neural networks." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066551/document.

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Cette thèse porte sur l'obtention rigoureuse de limites de champ moyen pour la dynamique continue de grands réseaux de neurones hétérogènes. Nous considérons des neurones à taux de décharge, et sujets à un bruit Brownien additif. Le réseau est entièrement connecté, avec des poids de connections dont la variance décroît comme l'inverse du nombre de neurones conservant un effet non trivial dans la limite thermodynamique. Un second type d'hétérogénéité, interprété comme une position spatiale, est considéré au niveau de chaque cellule. Pour la pertinence biologique, nos modèles incluent ou bien de

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Zhao, Qiwei. "Federated Learning with Heterogeneous Challenge." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/27399.

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Federated learning allows the training of a model from the distributed data of many clients under the orchestration of a central server. With the increasing concern on privacy, federated learning draws great attention from both academia and industry. However, the heterogeneous challenges introduced by natural characters of federated learning settings significantly degrade the performance of federated learning methods. Specifically, these heterogeneous challenges include the heterogeneous data challenges and the heterogeneous scenario challenges. Data heterogeneous challenges mean the signif

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Schliebs, Stefan. "Heterogeneous probabilistic models for optimisation and modelling of evolving spiking neural networks." AUT University, 2010. http://hdl.handle.net/10292/963.

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This thesis proposes a novel feature selection and classification method employing evolving spiking neural networks (eSNN) and evolutionary algorithms (EA). The method is named the Quantum-inspired Spiking Neural Network (QiSNN) framework. QiSNN represents an integrated wrapper approach. An evolutionary process evolves appropriate feature subsets for a given classification task and simultaneously optimises the neural and learning-related parameters of the network. Unlike other methods, the connection weights of this network are determined by a fast one-pass learning algorithm which dramaticall

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Antoniou, Christos Andrea. "Improving the acoustic modelling of speech using modular/ensemble combinations of heterogeneous neural networks." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340582.

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Wilson, Daniel B. "Combining genetic algorithms and artificial neural networks to select heterogeneous dispatching rules for a job shop system." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1177701025.

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Hobro, Mark. "Semantic Integration across Heterogeneous Databases : Finding Data Correspondences using Agglomerative Hierarchical Clustering and Artificial Neural Networks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-226657.

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The process of data integration is an important part of the database field when it comes to database migrations and the merging of data. The research in the area has grown with the addition of machine learning approaches in the last 20 years. Due to the complexity of the research field, no go-to solutions have appeared. Instead, a wide variety of ways of enhancing database migrations have emerged. This thesis examines how well a learning-based solution performs for the semantic integration problem in database migrations. Two algorithms are implemented. One that is based on information retrieva

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Tekleyohannes, Anteneh Tesfaye. "Unified and heterogeneous modeling of water vapour sorption in Douglas-fir wood with artificial neural networks." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/23032.

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The objective of this study was firstly to investigate and understand sorption properties of earlywood, latewood, annual rings and gross wood. Secondly, to develop a heterogeneous sorption model for earlywood, latewood and annual rings by taking into consideration unified complex interactions of anatomy, chemical composition and thermodynamic parameters. Thirdly, to upscale the annual ring level model to gross wood by applying artificial neural networks (ANNs) modeling tools using dimensionally reduced inputs through dimensional analysis and genetic algorithms. Four novel physical models, na

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Toledo, Testa Juan Ignacio. "Information extraction from heterogeneous handwritten documents." Doctoral thesis, Universitat Autònoma de Barcelona, 2019. http://hdl.handle.net/10803/667388.

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L’objectiu d’aquesta tesi és l’extracció d’Informació de documents total o parcialment manuscrits amb una certa estructura. Bàsicament treballem amb dos escenaris d’aplicació diferent. El primer escenari són els documents moderns altament estructurats, com formularis. En aquests documents, la informació semàntica està ja definida en camps, amb una posició concreta al document i l’extracció de la informació és equivalent a una transcripció. El segon escenari son els documents semi-estructurats totalment manuscrits on, a més de transcriure, cal associar un valor semàntic, d’entre un conjunt cone

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Calabuig, Soler Daniel. "Common Radio Resource Management Strategies for Quality of Service Support in Heterogeneous Wireless Networks." Doctoral thesis, Universitat Politècnica de València, 2010. http://hdl.handle.net/10251/7348.

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Hoy en día existen varias tecnologías que coexisten en una misma zona formando un sistema heterogéneo. Además, este hecho se espera que se vuelva más acentuado con todas las nuevas tecnologías que se están estandarizando actualmente. Hasta ahora, generalmente son los usuarios los que eligen la tecnología a la que se van a conectar, ya sea configurando sus terminales o usando terminales distintos. Sin embargo, esta solución es incapaz de aprovechar al máximo todos los recursos. Para ello es necesario un nuevo conjunto de estrategias. Estas estrategias deben gestionar los recursos radioeléctrico

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Ali, Muhammad. "Load balancing in heterogeneous wireless communications networks : optimized load aware vertical handovers in satellite-terrestrial hybrid networks incorporating IEEE 802.21 media independent handover and cognitive algorithms." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/6307.

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Heterogeneous wireless networking technologies such as satellite, UMTS, WiMax and WLAN are being used to provide network access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the 'Always Best Connected' paradigm whereby the mobile nodes are always directed towards the available network which has the strongest and fastest link. Hence a large number of mobile users may be connected

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LIMA, Natália Flora De. "Frankenstein PSO na definição das arquiteturas e ajustes dos pesos e uso de PSO heterogêneo no treinamento de redes neurais feed-forward." Universidade Federal de Pernambuco, 2011. https://repositorio.ufpe.br/handle/123456789/17738.

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Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2016-08-24T17:35:05Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao-Natalia_Flora_de_Lima.pdf: 2000980 bytes, checksum: 107f0691d21b9d94e253d08f06a4fbdd (MD5)<br>Made available in DSpace on 2016-08-24T17:35:05Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao-Natalia_Flora_de_Lima.pdf: 2000980 bytes, checksum: 107f0691d21b9d94e253d08f06a4fbdd (MD5) Previous issue date: 2011-08-29<br>Facepe<br>Este trabalho apresen

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Zhang, Wuming. "Towards non-conventional face recognition : shadow removal and heterogeneous scenario." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEC030/document.

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Ces dernières années, la biométrie a fait l’objet d’une grande attention en raison du besoin sans cesse croissant d’authentification d’identité, notamment pour sécuriser de plus en plus d’applications enlignes. Parmi divers traits biométriques, le visage offre des avantages compétitifs sur les autres, e.g., les empreintes digitales ou l’iris, car il est naturel, non-intrusif et facilement acceptable par les humains. Aujourd’hui, les techniques conventionnelles de reconnaissance faciale ont atteint une performance quasi-parfaite dans un environnement fortement contraint où la pose, l’éclairage,

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Ritholtz, Lee. "Intelligent text recognition system on a heterogeneous multi-core processor cluster a performance profile and architecture exploration /." Diss., Online access via UMI:, 2009.

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Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Electrical and Computer Engineering, 2009.<br>Includes bibliographical references.

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Westphal, Florian. "Efficient Document Image Binarization using Heterogeneous Computing and Interactive Machine Learning." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16797.

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Large collections of historical document images have been collected by companies and government institutions for decades. More recently, these collections have been made available to a larger public via the Internet. However, to make accessing them truly useful, the contained images need to be made readable and searchable. One step in that direction is document image binarization, the separation of text foreground from page background. This separation makes the text shown in the document images easier to process by humans and other image processing algorithms alike. While reasonably well worki

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Ong, Felicia Li Chin. "Heterogeneous Networking for Beyond 3G system in a High-Speed Train Environment. Investigation of handover procedures in a high-speed train environment and adoption of a pattern classification neural-networks approach for handover management." Thesis, University of Bradford, 2016. http://hdl.handle.net/10454/12341.

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Based on the targets outlined by the EU Horizon 2020 (H2020) framework, it is expected that heterogeneous networking will play a crucial role in delivering seamless end-to-end ubiquitous Internet access for users. In due course, the current GSM-Railway (GSM-R) will be deemed unsustainable, as the demand for packet-oriented services continues to increase. Therefore, the opportunity to identify a plausible replacement system conducted in this research study is timely and appropriate. In this research study, a hybrid satellite and terrestrial network for enabling ubiquitous Internet access in a h

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Bradley, Patrick Justin. "Heterogeneously coupled neural oscillators." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33938.

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The work we present in this thesis is a series of studies of how heterogeneities in coupling affect the synchronization of coupled neural oscillators. We begin by examining how heterogeneity in coupling strength affects the equilibrium phase difference of a pair of coupled, spiking neurons when compared to the case of identical coupling. This study is performed using pairs of Hodgkin-Huxley and Wang-Buzsaki neurons. We find that heterogeneity in coupling strength breaks the symmetry of the bifurcation diagrams of equilibrium phase difference versus the synaptic rate constant for weakly coup

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Martignano, Anna. "Real-time Anomaly Detection on Financial Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281832.

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This work presents an investigation of tailoring Network Representation Learning (NRL) for an application in the Financial Industry. NRL approaches are data-driven models that learn how to encode graph structures into low-dimensional vector spaces, which can be further exploited by downstream Machine Learning applications. They can potentially bring a lot of benefits in the Financial Industry since they extract in an automatic way features that can provide useful input regarding graph structures, called embeddings. Financial transactions can be represented as a network, and through NRL, it is

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Diaz, Boada Juan Sebastian. "Polypharmacy Side Effect Prediction with Graph Convolutional Neural Network based on Heterogeneous Structural and Biological Data." Thesis, KTH, Numerisk analys, NA, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288537.

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The prediction of polypharmacy side effects is crucial to reduce the mortality and morbidity of patients suffering from complex diseases. However, its experimental prediction is unfeasible due to the many possible drug combinations, leaving in silico tools as the most promising way of addressing this problem. This thesis improves the performance and robustness of a state-of-the-art graph convolutional network designed to predict polypharmacy side effects, by feeding it with complexity properties of the drug-protein network. The modifications also involve the creation of a direct pipeline to re

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Nguyen, Thanh Hai. "Some contributions to deep learning for metagenomics." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS102.

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Les données métagénomiques du microbiome humain constituent une nouvelle source de données pour améliorer le diagnostic et le pronostic des maladies humaines. Cependant, réaliser une prédiction basée sur l'abondance de bactéries individuelles est un défi, car le nombre de caractéristiques est beaucoup plus grand que le nombre d'échantillons et les difficultés liées au traitement de données dimensionnelles, ainsi que la grande complexité des données hétérogènes. L'apprentissage automatique a obtenu de grandes réalisations sur d'importants problèmes de métagénomique liés au regroupement d'OTU, à

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Bailey, Tony J. "Neuromorphic Architecture with Heterogeneously Integrated Short-Term and Long-Term Learning Paradigms." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1554217105047975.

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Liu, Chang. "Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334.

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Nowadays, the ideas of continuous integration and continuous delivery are under heavy usage in order to achieve rapid software development speed and quick product delivery to the customers with good quality. During the process ofmodern software development, the testing stage has always been with great significance so that the delivered software is meeting all the requirements and with high quality, maintainability, sustainability, scalability, etc. The key assignment of software testing is to find bugs from every test and solve them. The developers and test engineers at Ericsson, who are worki

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PETRINI, ALESSANDRO. "HIGH PERFORMANCE COMPUTING MACHINE LEARNING METHODS FOR PRECISION MEDICINE." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/817104.

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La Medicina di Precisione (Precision Medicine) è un nuovo paradigma che sta rivoluzionando diversi aspetti delle pratiche cliniche: nella prevenzione e diagnosi, essa è caratterizzata da un approccio diverso dal "one size fits all" proprio della medicina classica. Lo scopo delle Medicina di Precisione è di trovare misure di prevenzione, diagnosi e cura che siano specifiche per ciascun individuo, a partire dalla sua storia personale, stile di vita e fattori genetici. Tre fattori hanno contribuito al rapido sviluppo della Medicina di Precisione: la possibilità di generare rapidamente ed econo

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Galbincea, Nicholas D. "Critical Analysis of Dimensionality Reduction Techniques and Statistical Microstructural Descriptors for Mesoscale Variability Quantification." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500642043518197.

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"Heterogeneous neural networks: theory and applications." Universitat Politècnica de Catalunya, 2000. http://www.tesisenxarxa.net/TDX-0302109-114922/.

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Su, Yu-Sheng, and 蘇裕勝. "Heterogeneous Graph Embedding Based on Graph Convolutional Neural Networks." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/222yfr.

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碩士<br>國立政治大學<br>資訊科學系<br>108<br>In recent years, information network embedding has become popular because the techniques enable to encode information into low-dimensions representation, even for a graph/network with multiple types of nodes and relations. In addition, graph neural network (GNN) has also shown its effectiveness in learning large-scale node representations on node classification. In this paper, therefore, we propose a framework based on the heterogeneous network embedding and the idea of graph neural network. In our framework, we first generate node representations by various net

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Marques, José Fernando Duarte. "Distributed Learning of Convolutional Neural Networks on Heterogeneous Processing Units." Master's thesis, 2016. http://hdl.handle.net/10316/41280.

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The field of deep learning has been the focus of plenty of research and development over the last years. Deep Neural Networks (DNNs), and more specifically Convolutional Neural Networks (CNNs) have shown to be powerful tools in tasks that range from ordinary, like check reading, to the most essential, being used in medical diagnosis. This evolution in the field has lead to the development of frameworks, such as Torch and Theano, that simplified the training process of a CNN, where the user only needs to create the network architecture, select the ideal hyper-parameters and provide the inp

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Mahapatra, Dheeren Ku. "Modelling of Heterogeneous SAR Clutter for Speckle Suppression using MAP Estimation." Thesis, 2019. http://ethesis.nitrkl.ac.in/9865/1/2019_PHD_DKMahapatra_513EC1003_Modelling.pdf.

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Synthetic Aperture Radar (SAR) is an active high resolution imaging system that has been used intensively in diverse applications such as surveillance, environmental monitoring, urban planning, agriculture assessment etc. However, coherent nature of the SAR imaging system makes it highly susceptible to a multiplicative granular effect known as ‘Speckle’. The inherent presence of such speckle results in significant loss of relevant information (local mean of backscatter, point targets, texture etc.) which in turn makes interpretation and processing of SAR data difficult to human interpreters as

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Silva, Juliana Couras Fernandes. "A theory of spike coding networks with heterogeneous postsynaptic potentials." Master's thesis, 2021. http://hdl.handle.net/10773/32002.

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Modeling biologically realistic neural networks is a challenge for neural theory. While there is increasing evidence that the precise times of spikes play a crucial role in neural computation, building spike neural networks that resemble the spiking variability encountered in vivo while computing some function is not a trivial task. Boerlin et al. suggested a framework of leaky integrate-and-fire networks that, through excitation-inhibition tight balance, can track high-dimensional signals while producing spike trains with Poisson-like statistics. Notwithstanding their biologically plau

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Salamat, Amirreza. "Heterogeneous Graph Based Neural Network for Social Recommendations with Balanced Random Walk Initialization." Thesis, 2020. http://hdl.handle.net/1805/24769.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Research on social networks and understanding the interactions of the users can be modeled as a task of graph mining, such as predicting nodes and edges in networks. Dealing with such unstructured data in large social networks has been a challenge for researchers in several years. Neural Networks have recently proven very successful in performing predictions on number of speech, image, and text data and have become the de facto method when dealing with such data in a large volume. Graph NeuralNetworks, however, have only recently bec

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(9740444), Amirreza Salamat. "Heterogeneous Graph Based Neural Network for Social Recommendations with Balanced Random Walk Initialization." Thesis, 2021.

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Research on social networks and understanding the interactions of the users can be modeled as a task of graph mining, such as predicting nodes and edges in networks.Dealing with such unstructured data in large social networks has been a challenge for researchers in several years. Neural Networks have recently proven very successful in performing predictions on number of speech, image, and text data and have become the de facto method when dealing with such data in a large volume. Graph NeuralNetworks, however, have only recently become mature enough to be used in real large-scale graph predict

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Alhubail, Ali. "Application of Physics-Informed Neural Networks to Solve 2-D Single-phase Flow in Heterogeneous Porous Media." Thesis, 2021. http://hdl.handle.net/10754/670174.

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Neural networks have recently seen tremendous advancements in applicability in many areas, one of which is their utilization in solving physical problems governed by partial differential equations and the constraints of these equations. Physics-informed neural networks is the name given to such neural networks. They are different from typical neural networks in that they include loss terms that represent the physics of the problem. These terms often include partial derivatives of the neural network outputs with respect to its inputs, and these derivatives are found through the use of au

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Mittal, Divyansh. "Robustness of Neural Activity Dynamics in the Medial Entorhinal Cortex." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5808.

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Biological systems exhibit considerable heterogeneity in their constitutive components and encounter stochasticity across all scales of analysis. Therefore, central questions that span all biological systems are: (a) How does the system manifest robustness in the face of parametric variability and stochasticity? (b) What are the mechanisms used by disparate biological systems to maintain the robustness of physiological outcomes? In this thesis, we chose the mammalian medial entorhinal cortex (MEC) as the model system to systematically study the principles that govern functional robustness acro

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CHU, CHIA-HO, and 朱佳荷. "Application of Neural Networks and Genetic Algorithm to Optimize the Heterogeneous Metals Welding Parameters of Magnesium and Copper." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/vya5st.

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碩士<br>華梵大學<br>工業工程與經營資訊學系碩士班<br>106<br>Lightweight and strong magnesium alloys and highly conductive copper are widely used in various fields of application. When joining the both, it is frequent to find brittle compound at the joint. Typically, the industries heavily depend on the experience of master welders but that often leads to wobbling quality and their experience is difficult to pass on, not to mention the multiple quality characteristics. For this, a process was developed in this study to resolve the multiple quality characteristics issue in the heterogeneous soldering between magnesi

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Adhatarao, Sripriya Srikant. "PHOENIX: A Premise to Reinforce Heterogeneous and Evolving Internet Architectures with Exemplary Applications." Thesis, 2020. http://hdl.handle.net/21.11130/00-1735-0000-0005-150A-9.

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Jiang, Xinxin. "Mining heterogeneous enterprise data." Thesis, 2018. http://hdl.handle.net/10453/129377.

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University of Technology Sydney. Faculty of Engineering and Information Technology.<br>Heterogeneity is becoming one of the key characteristics inside enterprise data, because the current nature of globalization and competition stress the importance of leveraging huge amounts of enterprise accumulated data, according to various organizational processes, resources and standards. Effectively deriving meaningful insights from complex large-scaled heterogeneous enterprise data poses an interesting, but critical challenge. The aim of this thesis is to investigate the theoretical foundations of mini

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Chia-Pin, Wang, and 王嘉斌. "Neural-Network Based handoff algorithm to support QoS Multimedia application in Heterogeneous WLAN Environments." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/93139591775176572911.

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碩士<br>國立臺灣大學<br>電信工程學研究所<br>91<br>Abstract The integration of heterogeneous wireless access networks is expected in the future. It offers more selections of various services for mobile users. However, to support continuous link as mobile users roam in different networks, the handoff mechanism plays a very important role. Handoff mechanisms consist of handoff decision algorithms and handoff procedure algorithms. For real-time applications, handoff decision algorithm is much more critical because of its irretrievable property. As considering the heterogeneous wireless networks support

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Touati, Redha. "Détection de changement en imagerie satellitaire multimodale." Thèse, 2019. http://hdl.handle.net/1866/22662.

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The purpose of this research is to study the detection of temporal changes between two (or more) multimodal images satellites, i.e., between two different imaging modalities acquired by two heterogeneous sensors, giving for the same scene two images encoded differently and depending on the nature of the sensor used for each acquisition. The two (or multiple) multimodal satellite images are acquired and coregistered at two different dates, usually before and after an event. In this study, we propose new models belonging to different categories of multimodal change detection in remote sen

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