Search Results - (dynamic OR dynamik) graph conventional autoencoder

Multi-objective drug design with a scaffold-aware variational autoencoder by Dong, Tiejun, You, Linlin, Chen, Calvin Yu-Chian

“… To tackle this, we have developed ScafVAE, an innovative scaffold-aware variational autoencoder designed for the in silico graph-based generation of multi-objective drug candidates…”
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Spatio-temporal graph convolutional autoencoder for transonic wing pressure distribution forecasting by Immordino, Gabriele, Vaiuso, Andrea, Da Ronch, Andrea, Righi, Marcello

“…This study presents a framework for predicting unsteady transonic wing pressure distributions due to pitch and plunge movement, integrating an autoencoder architecture with graph convolutional…”
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Detection of False Data Injection Attacks in Cyber-Physical Power Systems: An Adaptive Adversarial Dual Autoencoder With Graph Representation Learning Approach by Feng, Hantong, Han, Yinghua, Si, Fangyuan, Zhao, Qiang

“… Inspired by the recent advances in deep learning, we propose a novel unsupervised method for FDIAs detection by combining the complementary strengths of dual graph-convolutional autoencoder (DAE…”
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Automated site layout generation for buildings using graph constrained generative adversarial network by Jiang, Ming, Chen, Yimin, Liu, Xiaoping, Gao, Jinding

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A survey on anomaly detection for technical systems using LSTM networks by Lindemann, Benjamin, Maschler, Benjamin, Sahlab, Nada, Weyrich, Michael

“… Conventional detection approaches rely on statistical and time-invariant methods that fail to address the complex and dynamic nature of anomalies…”
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Entropy-enhanced batch sampling and conformal learning in VGAE for physics-informed causal discovery and fault diagnosis by Modirrousta, Mohammadhossein, Memarian, Alireza, Huang, Biao

“…) in complex industrial processes. This research introduces a novel approach to causal discovery and FDD using Variational Graph Autoencoders (VGAEs…”
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Multi-Task Graph Attention Net for Electricity Consumption Prediction and Anomaly Detection by Bai, Na, Zhang, Jian, Wu, Zhaoli

“… these dynamic variations or quantify environmental impacts. This limitation results in a compromised prediction accuracy and ambiguous anomaly identification…”
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Open-world structured sequence learning via dense target encoding by Zhang, Qin, Liu, Ziqi, Li, Qincai, Xiang, Haolong, Yu, Zhizhi, Chen, Junyang, Zhang, Peng, Chen, Xiaojun

“…Structured sequences are popularly used to describe graph data with time-evolving node features and edges…”
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Quantum deep learning-enhanced ethereum blockchain for cloud security: intrusion detection, fraud prevention, and secure data migration by Nagarjun, A. Venkata, Rajkumar, Sujatha

“… Conventional blockchain security methods suffer from poor scalability and dynamic threat analysis…”
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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…Modern dynamic systems, such as transportation networks and IoT infrastructures, generate massive volumes of interrelated temporal data represented as temporal graphs…”
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Real-Time Anomalous Activity Detection in Surveillance Videos by Susitra, D, Reddy, Sathi Abhinay, Prasanth, Sajjala, Dhanalakshmi, K, J, Sylvia Grace, Shamreen Ahamed, B

“… In this paper, a robust spatio temporal auto encoder framework that takes advantage of spatial structure as well as temporal dynamics in video sequences and dynamic thresholding for anomaly detection is developed…”
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Variational Graph Convolutional Networks for Dynamic Graph Representation Learning by Mir, Aabid A., Zuhairi, Megat F., Musa, Shahrulniza, Alanazi, Meshari H., Namoun, Abdallah

“…The ubiquitous and ever-evolving nature of cyber threats demands innovative approaches that can adapt to the dynamic relationships and structures within network data…”
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DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads by Song, Kailu, Zheng, Yumin, Zhao, Bowen, Eidelman, David H., Tang, Jian, Ding, Jun

“… These graphs are processed by a variational graph autoencoder to improve cell embeddings. DOLPHIN not only demonstrates superior performance in cell…”
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Uncertainty-Aware Fault Diagnosis of Rotating Compressors Using Dual-Graph Attention Networks by Lee, Seungjoo, Kim, YoungSeok, Choi, Hyun-Jun, Ji, Bongjun

“… While Graph Attention Network (GAT) frameworks are widely available, this study advances the state of the art by introducing a Bayesian GAT method specifically tailored for vibration-based compressor fault diagnosis…”
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Latent‐space Dynamics for Reduced Deformable Simulation by Fulton, Lawson, Modi, Vismay, Duvenaud, David, Levin, David I. W., Jacobson, Alec

“…We propose the first reduced model simulation framework for deformable solid dynamics using autoencoder neural networks. We provide a data…”
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Robust Wireless Localization in UAV Swarm Networks: A Deep-Graph-Generator-Assisted Convex Optimization Approach by Chen, Yu-Jia, Huang, Hai-Yan, Chen, Min-Wei, Ku, Meng-Lin

“… However, conventional global positioning system or radio frequency-based localization systems often do not function effectively in highly dynamic and unstable mobile ad-hoc environments…”
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Collaborative optimization of dynamic early warning and control in desulphurization process via integration of causal inference and temporal features by Li, He, Yang, Bozhi, Gu, Xinyu

“…The inherent time‐lag effects, nonlinear dependencies, and dynamic coupling mechanisms in desulphurization processes pose significant challenges to precise quality prediction and proactive control…”
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DeepCovPG:Deep-Learning-based Dynamic Covariance Prediction in Pose Graphs for Ultra-Wideband-Aided UAV Positioning by Arjmandi, Zahra, Kang, Jungwon, Sohn, Gunho, Armenakis, Costas, Shahbazi, Mozhdeh

“… This approach integrates a dynamic covariance model within the pose graph optimization process, diverges from conventional static uncertainty approaches, enhancing adaptability to environmental…”
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Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality by Liu, Jie, Shang, Xuequn, Han, Xiaolin, Zheng, Kai, Yin, Hongzhi

“…Anomaly detection in dynamic graphs presents a significant challenge due to the temporal evolution of graph structures and attributes…”
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Editorial by Gütl, Christian

“…Dear Readers, Welcome to another J.UCS regular issue covering 5 articles on topical research areas in computer science. As part of our continuous improvement…”
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