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Variation of Velocity Distribution in Rough Meandering Channels
Published 2018-01-01Get full text
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In silico detection of sequence variations modifying transcriptional regulation.
Published 2008-01-01Get full text
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Landscape and variation of novel retroduplications in 26 human populations.
Published 2017-06-01Get full text
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Piezoelectric neuron for neuromorphic computing
Published 2025-09-01“…Neuromorphic computing has attracted great attention for its massive parallelism and high energy efficiency. …”
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Classical simulations of noisy variational quantum circuits
Published 2025-05-01Get full text
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AD-VAE: Adversarial Disentangling Variational Autoencoder
Published 2025-03-01Get full text
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Research on the Application of Variational Autoencoder in Image Generation
Published 2025-01-01“…This paper concentrates on applying Variational Autoencoders (VAEs) to image generation, a topic of increasing importance due to the model’s theoretical interpretability and stability. …”
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Tseng-Type Algorithms for the Split Variational Inclusion
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On Dichotomous Behavior of Variational Difference Equations and Applications
Published 2009-01-01Get full text
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On the cross-variation of a class of stochastic processes
Published 2024-11-01Get full text
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An Approximation Method for Variational Inequality with Uncertain Variables
Published 2023-01-01Get full text
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Implicit Iterative Method for Hierarchical Variational Inequalities
Published 2012-01-01Get full text
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On Anisotropic Variational Model for SAR Image Despeckling
Published 2025-04-01Get full text
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Overcoming Language Variation in Sentiment Analysis with Social Attention
Published 2021-03-01Get full text
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Meta-learning approach for variational autoencoder hyperparameter tuning
Published 2025-06-01“…Synthetic data generation is a promising alternative to traditional data anonymization, with Variational Autoencoders (VAEs) excelling at generating high-quality synthetic tabular datasets. …”
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A Clustering Algorithm for Large Datasets Based on Detection of Density Variations
Published 2025-07-01“…Within each partition, relevant objects subsets characterized by attributes such as density, position, and overlap ratio are computed to identify both low-density regions and density variations, thereby facilitating the building of the clusters. …”
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Online variational Gaussian process for time series data
Published 2024-12-01“…However, traditional GP methods are often hindered by cubic computational complexity, making them impractical for the massive and potentially unbounded datasets commonly encountered in IoT applications. …”
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