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Computational Science – ICCS 2020
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Advances in High-Performance Computational Earth Sciences: Applications and Frameworks.- Data-Driven Approach to Inversion Analysis of Three-dimensional Inner Soil Structure via Wave Propagation Analysis.- Data assimilation in volcano deformation using fast finite element analysis with high fidelity model.- Optimization and Local Time Stepping of an ADER-DG Scheme for Fully Anisotropic Wave Propagation in Complex Geometries.- The challenge of onboard SAR processing: a GPU opportunity.- High-resolution Source Estimation of Volcanic Sulfur Dioxide Emissions Using Large Scale Transport Simulations.- Granulation-based reverse image retrieval for microscopic rock images.- Hybrid SWAN for fast and efficient practical wave modelling - part 2.- Agent-Based Simulations, Adaptive Algorithms and Solvers.- An agent-based simulation of the spread of Dengue fever.- Hypergraph grammar-based model of adaptive bitmap compression.- Simulation of Neurotransmitter Flow in Three Dimensional Model of Presynaptic Bouton.- Scalable Signal-based Simulation of Autonomous Beings in Complex Environments.- Design of Loss Functions for Solving Inverse Problems using Deep Learning.- Asynchronous Actor-based Approach to Multiobjective Hierarchical Strategy.- MeshingNet: A New Mesh Generation Method based on Deep Learning.- A block preconditioner for scalable large scale finite element incompressible flow simulations.- Integrating Agent-Based Modelling with Copula Theory: Preliminary Insights and Open Problems.- Computational complexity of hierarchically adapted meshes.- A Novel Bio-inspired Hybrid Metaheuristic for Unsolicited Bulk Email Detection.- Applications of Computational Methods in Artificial Intelligence and Machine Learning.- Link Prediction by Analyzing Temporal Behavior of Vertices.- Detecting Most Insightful Parts of Documents using an Attention-Based Model.- Challenge Collapsar(CC) Attack Traffic Detection based on Packet Field Differentiated Preprocessing and Deep Neural Network.- Deep Low-Density Separation for Semi-Supervised Classification.- Learning functions using data-dependent regularization: Representer theorem revisited.- Reduction of Numerical Errors in Zernike Invariants Computed via Complex-Valued Integral Images.- Effect of Dataset Size on Efficiency of Collaborative Filtering Recommender Systems with Multi-Clustering as a Neighbourhood Identification Strategy.- GCN-IA: User Profile Based on Graph Convolutional Network with Implicit Association Labels.- Interval AdjointSignificance Analysis for Neural Networks.- Ringer: Systematic Mining of Malicious Domains by Dynamic Graph Convolutional Network.- An Empirical Evaluation Of Attention And Pointer Networks For Paraphrase Generation.- Interval methods for seeking fixed points of recurrent neural networks.- Fusion Learning: A One Shot Federated Learning.- The concept of system for automated scientific literature reviews generation.- A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings.- Retrain or not retrain ? - efficient pruning methods of deep CNN networks.- Hidden Markov Models and their Application for Predicting Failure Events.- Biomedical and Bioinformatics Challenges for Computer Science.- Reference-based Haplotype Phasing with FPGAs.- Tree Based Advanced Relative Expression Analysis.- Testing the significance of interactions in genetic studies using interaction information and resampling technique.- Analysis of ensemble feature selection for correlated high-dimensional RNA-Seq cancer data.- Biological Network Visualization for Targeted Proteomics based on Mean First-Passage Time in Semi-Lazy Random Walks.- Bootstrap Bias Corrected Cross Validation applied to Super Learning.- MMRF-CoMMpass data integration and analysis for identifying prognostic markers.- Using machine learning in accuracy assessment of knowledge-based energy and frequency base likelihood in protein structures.- Quantifying Overfitting Potential in Drug Binding Datasets.- Detection of Tumoral Epithelial Lesions Using Hyperspectral Imaging and Deep Learning.- Statistical iterative reconstruction algorithm based on a continuous-tocontinuous model formulated for spiral cone-beam CT.- Classification of lung diseases using deep learning models.- An Adaptive Space-Filling Curve Trajectory for Mapping 3D Datasets to 1D: Application to Brain Magnetic Resonance Imaging Data for Classification.

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