Saved in:
| Main Authors: | Cai, Yuxi, Li, Lan, Huang, Feiqing, Li, Guodong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.02692 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models
by: Danieli, Federico, et al.
Published: (2025)
by: Danieli, Federico, et al.
Published: (2025)
TA-RNN: an Attention-based Time-aware Recurrent Neural Network Architecture for Electronic Health Records
by: Olaimat, Mohammad Al, et al.
Published: (2024)
by: Olaimat, Mohammad Al, et al.
Published: (2024)
Contrastive Learning on Multimodal Analysis of Electronic Health Records
by: Cai, Tianxi, et al.
Published: (2024)
by: Cai, Tianxi, et al.
Published: (2024)
An Efficient and Interpretable Autoregressive Model for High-Dimensional Tensor-Valued Time Series
by: Cai, Yuxi, et al.
Published: (2025)
by: Cai, Yuxi, et al.
Published: (2025)
Parallelizable memory recurrent units
by: De Geeter, Florent, et al.
Published: (2026)
by: De Geeter, Florent, et al.
Published: (2026)
GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting Blood Glucose Levels via Multivariate Time Series
by: Piao, Chengzhe, et al.
Published: (2024)
by: Piao, Chengzhe, et al.
Published: (2024)
Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations
by: Chen, Yuan, et al.
Published: (2025)
by: Chen, Yuan, et al.
Published: (2025)
Continuous-Time Piecewise-Linear Recurrent Neural Networks
by: Brändle, Alena, et al.
Published: (2026)
by: Brändle, Alena, et al.
Published: (2026)
Time-Warping Recurrent Neural Networks for Transfer Learning
by: Hirschi, Jonathon
Published: (2026)
by: Hirschi, Jonathon
Published: (2026)
Attention as an RNN
by: Feng, Leo, et al.
Published: (2024)
by: Feng, Leo, et al.
Published: (2024)
Generalization and Risk Bounds for Recurrent Neural Networks
by: Cheng, Xuewei, et al.
Published: (2024)
by: Cheng, Xuewei, et al.
Published: (2024)
Why Are Linear RNNs More Parallelizable?
by: Merrill, William, et al.
Published: (2026)
by: Merrill, William, et al.
Published: (2026)
Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks
by: Massey, Andreas, et al.
Published: (2026)
by: Massey, Andreas, et al.
Published: (2026)
HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks
by: Chen, Yuanyuan, et al.
Published: (2021)
by: Chen, Yuanyuan, et al.
Published: (2021)
IRNN: Innovation-driven Recurrent Neural Network for Time-Series Data Modeling and Prediction
by: Zhou, Yifan, et al.
Published: (2025)
by: Zhou, Yifan, et al.
Published: (2025)
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers
by: Chen, Xuexin, et al.
Published: (2025)
by: Chen, Xuexin, et al.
Published: (2025)
Mini-Hes: A Parallelizable Second-order Latent Factor Analysis Model
by: Wang, Jialiang, et al.
Published: (2024)
by: Wang, Jialiang, et al.
Published: (2024)
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks
by: Michałowska, Katarzyna, et al.
Published: (2023)
by: Michałowska, Katarzyna, et al.
Published: (2023)
Deep State Space Recurrent Neural Networks for Time Series Forecasting
by: Inzirillo, Hugo
Published: (2024)
by: Inzirillo, Hugo
Published: (2024)
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
by: Wang, Shida, et al.
Published: (2023)
by: Wang, Shida, et al.
Published: (2023)
ISMRNN: An Implicitly Segmented RNN Method with Mamba for Long-Term Time Series Forecasting
by: Zhao, GaoXiang, et al.
Published: (2024)
by: Zhao, GaoXiang, et al.
Published: (2024)
A Disentangled Low-Rank RNN Framework for Uncovering Neural Connectivity and Dynamics
by: Li, Chengrui, et al.
Published: (2025)
by: Li, Chengrui, et al.
Published: (2025)
Interpretable Graph Neural Networks for Heterogeneous Tabular Data
by: Alkhatib, Amr, et al.
Published: (2024)
by: Alkhatib, Amr, et al.
Published: (2024)
Towards Interpretable Deep Neural Networks for Tabular Data
by: Elhadri, Khawla, et al.
Published: (2025)
by: Elhadri, Khawla, et al.
Published: (2025)
RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks
by: Hou, Haowen, et al.
Published: (2024)
by: Hou, Haowen, et al.
Published: (2024)
Fourier-Enhanced Recurrent Neural Networks for Electrical Load Time Series Downscaling
by: Chen, Qi, et al.
Published: (2025)
by: Chen, Qi, et al.
Published: (2025)
CONFINE: Conformal Prediction for Interpretable Neural Networks
by: Huang, Linhui, et al.
Published: (2024)
by: Huang, Linhui, et al.
Published: (2024)
Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)
by: Furuya, Takashi, et al.
Published: (2021)
Investigating Sparsity in Recurrent Neural Networks
by: Darji, Harshil
Published: (2024)
by: Darji, Harshil
Published: (2024)
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
by: Erichson, N. Benjamin, et al.
Published: (2022)
by: Erichson, N. Benjamin, et al.
Published: (2022)
Interpretable Graph Neural Networks for Tabular Data
by: Alkhatib, Amr, et al.
Published: (2023)
by: Alkhatib, Amr, et al.
Published: (2023)
TA-RNN-Medical-Hybrid: A Time-Aware and Interpretable Framework for Mortality Risk Prediction
by: Jafari, Zahra, et al.
Published: (2026)
by: Jafari, Zahra, et al.
Published: (2026)
Data-Driven Dynamic Friction Models based on Recurrent Neural Networks
by: Cortes, Gaëtan, et al.
Published: (2024)
by: Cortes, Gaëtan, et al.
Published: (2024)
Time-Scale Coupling Between States and Parameters in Recurrent Neural Networks
by: Livi, Lorenzo
Published: (2025)
by: Livi, Lorenzo
Published: (2025)
Massive Activations in Graph Neural Networks: Decoding Attention for Domain-Dependent Interpretability
by: Bini, Lorenzo, et al.
Published: (2024)
by: Bini, Lorenzo, et al.
Published: (2024)
Unraveling the Hidden Dynamical Structure in Recurrent Neural Policies
by: Li, Jin, et al.
Published: (2026)
by: Li, Jin, et al.
Published: (2026)
Factor Graph-based Interpretable Neural Networks
by: Li, Yicong, et al.
Published: (2025)
by: Li, Yicong, et al.
Published: (2025)
When Learning Hurts: Fixed-Pole RNN for Real-Time Online Training
by: Morgan, Alexander, et al.
Published: (2026)
by: Morgan, Alexander, et al.
Published: (2026)
PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
by: Jia, Yuxin, et al.
Published: (2024)
by: Jia, Yuxin, et al.
Published: (2024)
Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections
by: Wagenländer, Marcel, et al.
Published: (2023)
by: Wagenländer, Marcel, et al.
Published: (2023)
Similar Items
-
ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models
by: Danieli, Federico, et al.
Published: (2025) -
TA-RNN: an Attention-based Time-aware Recurrent Neural Network Architecture for Electronic Health Records
by: Olaimat, Mohammad Al, et al.
Published: (2024) -
Contrastive Learning on Multimodal Analysis of Electronic Health Records
by: Cai, Tianxi, et al.
Published: (2024) -
An Efficient and Interpretable Autoregressive Model for High-Dimensional Tensor-Valued Time Series
by: Cai, Yuxi, et al.
Published: (2025) -
Parallelizable memory recurrent units
by: De Geeter, Florent, et al.
Published: (2026)