KoopAGRU: A Koopman-based Anomaly Detection in Time-Series using Gated Recurrent Units
Fuente:
arXiv
Saved in:
| Main Authors: | Yahia, Issam Ait, Berrada, Ismail |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DeepKoopFormer: A Koopman Enhanced Transformer Based Architecture for Time Series Forecasting
by: Forootani, Ali, et al.
Published: (2025)
by: Forootani, Ali, et al.
Published: (2025)
Deep Learning for Contextualized NetFlow-Based Network Intrusion Detection: Methods, Data, Evaluation and Deployment
by: Mahdaouy, Abdelkader El, et al.
Published: (2026)
by: Mahdaouy, Abdelkader El, et al.
Published: (2026)
KoopCast: Trajectory Forecasting via Koopman Operators
by: Lee, Jungjin, et al.
Published: (2025)
by: Lee, Jungjin, et al.
Published: (2025)
KoopGen: Koopman Generator Networks for Representing and Predicting Dynamical Systems with Continuous Spectra
by: Su, Liangyu, et al.
Published: (2026)
by: Su, Liangyu, et al.
Published: (2026)
ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
by: Xu, Yuanchao, et al.
Published: (2025)
by: Xu, Yuanchao, et al.
Published: (2025)
RoboKoop: Efficient Control Conditioned Representations from Visual Input in Robotics using Koopman Operator
by: Kumawat, Hemant, et al.
Published: (2024)
by: Kumawat, Hemant, et al.
Published: (2024)
KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning
by: Li, Alice Kate, et al.
Published: (2025)
by: Li, Alice Kate, et al.
Published: (2025)
Anomaly Detection for Non-stationary Time Series using Recurrent Wavelet Probabilistic Neural Network
by: Yang, Pu, et al.
Published: (2025)
by: Yang, Pu, et al.
Published: (2025)
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection
by: Le, Long Tan, et al.
Published: (2025)
by: Le, Long Tan, et al.
Published: (2025)
Minion Gated Recurrent Unit for Continual Learning
by: Zyarah, Abdullah M., et al.
Published: (2025)
by: Zyarah, Abdullah M., et al.
Published: (2025)
Cryptocurrency Price Prediction Using Parallel Gated Recurrent Units
by: Asadpour, Milad, et al.
Published: (2025)
by: Asadpour, Milad, et al.
Published: (2025)
A Representation-Consistent Gated Recurrent Framework for Robust Medical Time-Series Classification
by: Sai, Maitri Krishna
Published: (2026)
by: Sai, Maitri Krishna
Published: (2026)
Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection
by: Hammami, Wajdi, et al.
Published: (2025)
by: Hammami, Wajdi, et al.
Published: (2025)
Gate Recurrent Unit for Efficient Industrial Gas Identification
by: Wang, Ding
Published: (2024)
by: Wang, Ding
Published: (2024)
Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection
by: Lee, Ming-Chang, et al.
Published: (2024)
by: Lee, Ming-Chang, et al.
Published: (2024)
Koopman Ensembles for Probabilistic Time Series Forecasting
by: Frion, Anthony, et al.
Published: (2024)
by: Frion, Anthony, et al.
Published: (2024)
Graph Anomaly Detection in Time Series: A Survey
by: Ho, Thi Kieu Khanh, et al.
Published: (2023)
by: Ho, Thi Kieu Khanh, et al.
Published: (2023)
Explainable Time Series Anomaly Detection using Masked Latent Generative Modeling
by: Lee, Daesoo, et al.
Published: (2023)
by: Lee, Daesoo, et al.
Published: (2023)
Unified Taxonomy for Multivariate Time Series Anomaly Detection using Deep Learning
by: Alves, Bruna, et al.
Published: (2026)
by: Alves, Bruna, et al.
Published: (2026)
Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection
by: Yao, Yuanyuan, et al.
Published: (2025)
by: Yao, Yuanyuan, et al.
Published: (2025)
GRAD: Real-Time Gated Recurrent Anomaly Detection in Autonomous Vehicle Sensors Using Reinforced EMA and Multi-Stage Sliding Window Techniques
by: Naeimi, Mohammad Hossein Jafari, et al.
Published: (2025)
by: Naeimi, Mohammad Hossein Jafari, et al.
Published: (2025)
TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
by: Si, Haotian, et al.
Published: (2024)
by: Si, Haotian, et al.
Published: (2024)
Label-Free Multivariate Time Series Anomaly Detection
by: Zhou, Qihang, et al.
Published: (2023)
by: Zhou, Qihang, et al.
Published: (2023)
Contextual and Seasonal LSTMs for Time Series Anomaly Detection
by: Zhang, Lingpei, et al.
Published: (2026)
by: Zhang, Lingpei, et al.
Published: (2026)
Open-Set Multivariate Time-Series Anomaly Detection
by: Lai, Thomas, et al.
Published: (2023)
by: Lai, Thomas, et al.
Published: (2023)
Enhancing Bangla Fake News Detection Using Bidirectional Gated Recurrent Units and Deep Learning Techniques
by: Roy, Utsha, et al.
Published: (2024)
by: Roy, Utsha, et al.
Published: (2024)
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection
by: Zhong, Zhijie, et al.
Published: (2024)
by: Zhong, Zhijie, et al.
Published: (2024)
Transformer-based Multivariate Time Series Anomaly Localization
by: Shimillas, Charalampos, et al.
Published: (2025)
by: Shimillas, Charalampos, et al.
Published: (2025)
SCGNet-Stacked Convolution with Gated Recurrent Unit Network for Cyber Network Intrusion Detection and Intrusion Type Classification
by: Akter, Rajana, et al.
Published: (2024)
by: Akter, Rajana, et al.
Published: (2024)
Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management
by: Xu, Zhen, et al.
Published: (2024)
by: Xu, Zhen, et al.
Published: (2024)
Multivariate Time Series Anomaly Detection in Industry 5.0
by: Colombi, Lorenzo, et al.
Published: (2025)
by: Colombi, Lorenzo, et al.
Published: (2025)
Formally Exploring Time-Series Anomaly Detection Evaluation Metrics
by: Wagner, Dennis, et al.
Published: (2025)
by: Wagner, Dennis, et al.
Published: (2025)
Open Challenges in Time Series Anomaly Detection: An Industry Perspective
by: Mueller, Andreas
Published: (2025)
by: Mueller, Andreas
Published: (2025)
Unsupervised Feature Construction for Anomaly Detection in Time Series -- An Evaluation
by: Hamon, Marine, et al.
Published: (2025)
by: Hamon, Marine, et al.
Published: (2025)
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
by: Qiu, Xiangfei, et al.
Published: (2025)
by: Qiu, Xiangfei, et al.
Published: (2025)
Selective Denoising Diffusion Model for Time Series Anomaly Detection
by: Obata, Kohei, et al.
Published: (2026)
by: Obata, Kohei, et al.
Published: (2026)
MIXAD: Memory-Induced Explainable Time Series Anomaly Detection
by: Kim, Minha, et al.
Published: (2024)
by: Kim, Minha, et al.
Published: (2024)
Fortifying Time Series: DTW-Certified Robust Anomaly Detection
by: Liu, Shijie, et al.
Published: (2026)
by: Liu, Shijie, et al.
Published: (2026)
LLM-Enhanced Reinforcement Learning for Time Series Anomaly Detection
by: Golchin, Bahareh, et al.
Published: (2026)
by: Golchin, Bahareh, et al.
Published: (2026)
Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection
by: Wu, Zhangkai, et al.
Published: (2024)
by: Wu, Zhangkai, et al.
Published: (2024)
Similar Items
-
DeepKoopFormer: A Koopman Enhanced Transformer Based Architecture for Time Series Forecasting
by: Forootani, Ali, et al.
Published: (2025) -
Deep Learning for Contextualized NetFlow-Based Network Intrusion Detection: Methods, Data, Evaluation and Deployment
by: Mahdaouy, Abdelkader El, et al.
Published: (2026) -
KoopCast: Trajectory Forecasting via Koopman Operators
by: Lee, Jungjin, et al.
Published: (2025) -
KoopGen: Koopman Generator Networks for Representing and Predicting Dynamical Systems with Continuous Spectra
by: Su, Liangyu, et al.
Published: (2026) -
ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
by: Xu, Yuanchao, et al.
Published: (2025)