MSAFormer: A Transformer-Based Model for PM_2.5 Prediction Leveraging Sparse Autoencoding of Multi-Site Meteorological Features in Urban Areas by Hongqing Wang, Lifu Zhang, Rong Wu

Subjects: “…meteorological sparse autoencoding…”
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ReMODE: a deep learning-based web server for target-specific drug design by Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou

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Optimizing Few-Shot Learning Based on Variational Autoencoders by Ruoqi Wei, Ausif Mahmood

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Autoencoder-Based Neural Network Model for Anomaly Detection in Wireless Body Area Networks by Murad A. Rassam

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Detection and Classification of Knee Injuries from MR Images Using the MRNet Dataset with Progressively Operating Deep Learning Methods by Ali Can Kara, Fırat Hardalaç

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Generation of geometric interpolations of building types with deep variational autoencoders by Jaime de Miguel Rodríguez, Maria Eugenia Villafañe, Luka Piškorec, Fernando Sancho Caparrini

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Improving Variational Graph Autoencoders With Multi-Order Graph Convolutions by Lining Yuan, Ping Jiang, Zhu Wen, Jionghui Li

Subjects: “…Variational graph autoencoders…”
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Short-Term Wind-Speed Forecasting Based on Multiscale Mathematical Morphological Decomposition, K-Means Clustering, and Stacked Denoising Autoencoders by Weichao Dong, Hexu Sun, Zheng Li, Jingxuan Zhang, Huifang Yang

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Marginalised Stacked Denoising Autoencoders for Robust Representation of Real-Time Multi-View Action Recognition by Feng Gu, Francisco Flórez-Revuelta, Dorothy Monekosso, Paolo Remagnino

Subjects: “…marginalised stacked denoising autoencoders…”
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MURM: Utilization of Multi-Views for Goal-Conditioned Reinforcement Learning in Robotic Manipulation by Seongwon Jang, Hyemi Jeong, Hyunseok Yang

Subjects: “…vector-quantized variational autoencoders (VQVAE)…”
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Autoencoder-Based Reduced Order Observer Design for a Class of Diffusion-Convection-Reaction Systems by Alexander Schaum

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A Comparison of Machine Learning-Based and Conventional Technologies for Video Compression by Lesia Mochurad

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Harnessing Deep Convolutional Neural Networks Detecting Synthetic Cannabinoids: A Hybrid Learning Strategy for Handling Class Imbalances in Limited Datasets by Catalina Mercedes Burlacu, Adrian Constantin Burlacu, Mirela Praisler, Cristina Paraschiv

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A Multimodal Approach for Identifying Autism Spectrum Disorders in Children by Junxia Han, Guoqian Jiang, Gaoxiang Ouyang, Xiaoli Li

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Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues by Julie Sparholt Walbech, Savvas Kinalis, Ole Winther, Finn Cilius Nielsen, Frederik Otzen Bagger

Subjects: “…autoencoders (AE)…”
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Equipment Anomaly Detection for Semiconductor Manufacturing by Exploiting Unsupervised Learning from Sensory Data by Chieh-Yu Chen, Shi-Chung Chang, Da-Yin Liao

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Improving Chemical Autoencoder Latent Space and Molecular <i>De Novo</i> Generation Diversity with Heteroencoders by Esben Jannik Bjerrum, Boris Sattarov

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Innovative Topologies and Algorithms for Neural Networks by Salvatore Graziani, Maria Gabriella Xibilia

Subjects: “…autoencoders…”
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Detection of Marchiafava Bignami disease using distinct deep learning techniques in medical diagnostics by J. Satheesh Kumar, V. Vinoth Kumar, T. R. Mahesh, Mohammed S. Alqahtani, P. Prabhavathy, K. Manikandan, Suresh Guluwadi

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Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain by Hamza Kebiri, Hamza Kebiri, Erick J. Canales-Rodríguez, Hélène Lajous, Hélène Lajous, Priscille de Dumast, Priscille de Dumast, Gabriel Girard, Gabriel Girard, Gabriel Girard, Yasser Alemán-Gómez, Mériam Koob, András Jakab, András Jakab, Meritxell Bach Cuadra, Meritxell Bach Cuadra, Meritxell Bach Cuadra

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