mlsanityData to 7 Oct 2026

Complex Gated Recurrent Neural Networks

arXiv 1806.08267 ↗First posted 21 Jun 2018cs.LG stat.MLcited by 17

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Abstract (arXiv)

Complex numbers have long been favoured for digital signal processing, yet complex representations rarely appear in deep learning architectures. RNNs, widely used to process time series and sequence information, could greatly benefit from complex representations. We present a novel complex gated recurrent cell, which is a hybrid cell combining complex-valued and norm-preserving state transitions with a gating mechanism. The resulting RNN exhibits excellent stability and convergence properties and performs competitively on the synthetic memory and adding task, as well as on the real-world tasks of human motion prediction.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jun 2018.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 2; 2024: 2; 2025: 3; 2026: 2.

17 papers.

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  1. 2022Simplifying and Understanding State Space Models with Diagonal Linear RNNscited by 23
  2. 2024Language-Driven Interactive Traffic Trajectory Generationcited by 19
  3. 2021Towards Understanding Theoretical Advantages of Complex-Reaction Networkscited by 6
  4. 20223D Human Pose Estimation Using M"obius Graph Convolutional Networkscited by 6
  5. 2021Quantitative approximation results for complex-valued neural networkscited by 5
  6. 2025Revisiting Bi-Linear State Transitions in Recurrent Neural Networkscited by 4
  7. 2025A Survey of Deep Learning for Complex Speech Spectrogramscited by 3
  8. 2023Adapting Pre-trained Language Models for Quantum Natural Language Processingcited by 2
  9. 2023Physics-constrained Attack against Convolution-based Human Motion Predictioncited by 2
  10. 2025BeatFormer: Efficient motion-robust remote heart rate estimation through unsupervised spectral zoomed attention filterscited by 2
  11. 2022Fully complex-valued deep learning model for visual perceptioncited by 1
  12. 2026The Quantum Shortcut: Complex Phase-State Dynamics Reduce the Optimization Steps of Sequence Modelscited by 1
5 more
  1. 2021Neural Networks with Complex-Valued Weights Have No Spurious Local Minimacited by 0
  2. 2021FallDeF5: A Fall Detection Framework Using 5G-based Deep Gated Recurrent Unit Networkscited by 0
  3. 2021Acceleration Method for Learning Fine-Layered Optical Neural Networkscited by 0
  4. 2024BadHMP: Backdoor Attack against Human Motion Predictioncited by 0
  5. 2026Phase-Associative Memory: Sequence Modeling in Complex Hilbert Spacecited by 0