Saved in:
| Main Authors: | Zhang, Yuanhang, Lin, Zhidi, Sun, Yiyong, Yin, Feng, Fritsche, Carsten |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.10123 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference
by: Lin, Zhidi, et al.
Published: (2023)
by: Lin, Zhidi, et al.
Published: (2023)
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
by: Lin, Zhidi, et al.
Published: (2025)
by: Lin, Zhidi, et al.
Published: (2025)
Hybrid Data-Driven SSM for Interpretable and Label-Free mmWave Channel Prediction
by: Sun, Yiyong, et al.
Published: (2024)
by: Sun, Yiyong, et al.
Published: (2024)
Preventing Model Collapse in Gaussian Process Latent Variable Models
by: Li, Ying, et al.
Published: (2024)
by: Li, Ying, et al.
Published: (2024)
Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel
by: Suwandi, Richard Cornelius, et al.
Published: (2023)
by: Suwandi, Richard Cornelius, et al.
Published: (2023)
Learning Guarantee of Reward Modeling Using Deep Neural Networks
by: Luo, Yuanhang, et al.
Published: (2025)
by: Luo, Yuanhang, et al.
Published: (2025)
Unbiased Online Curvature Approximation for Regularized Graph Continual Learning
by: Yin, Jie, et al.
Published: (2025)
by: Yin, Jie, et al.
Published: (2025)
Learning Mamba as a Continual Learner: Meta-learning Selective State Space Models for Efficient Continual Learning
by: Zhao, Chongyang, et al.
Published: (2024)
by: Zhao, Chongyang, et al.
Published: (2024)
SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark
by: Wen, Rui, et al.
Published: (2025)
by: Wen, Rui, et al.
Published: (2025)
Deep Continuous-Time State-Space Models for Marked Event Sequences
by: Chang, Yuxin, et al.
Published: (2024)
by: Chang, Yuxin, et al.
Published: (2024)
Exemplar-Free Continual Learning for State Space Models
by: Lee, Isaac Ning, et al.
Published: (2025)
by: Lee, Isaac Ning, et al.
Published: (2025)
Deep Learning-based Approaches for State Space Models: A Selective Review
by: Lin, Jiahe, et al.
Published: (2024)
by: Lin, Jiahe, et al.
Published: (2024)
Revisiting Weight Regularization for Low-Rank Continual Learning
by: Zheng, Yaoyue, et al.
Published: (2026)
by: Zheng, Yaoyue, et al.
Published: (2026)
A Statistical Theory of Regularization-Based Continual Learning
by: Zhao, Xuyang, et al.
Published: (2024)
by: Zhao, Xuyang, et al.
Published: (2024)
Latent Matters: Learning Deep State-Space Models
by: Klushyn, Alexej, et al.
Published: (2026)
by: Klushyn, Alexej, et al.
Published: (2026)
Multi-View Oriented GPLVM: Expressiveness and Efficiency
by: Yang, Zi, et al.
Published: (2025)
by: Yang, Zi, et al.
Published: (2025)
Space-Filling Regularization for Robust and Interpretable Nonlinear State Space Models
by: Klein, Hermann, et al.
Published: (2025)
by: Klein, Hermann, et al.
Published: (2025)
Fixed Design Analysis of Regularization-Based Continual Learning
by: Li, Haoran, et al.
Published: (2023)
by: Li, Haoran, et al.
Published: (2023)
Scalable Random Feature Latent Variable Models
by: Li, Ying, et al.
Published: (2024)
by: Li, Ying, et al.
Published: (2024)
Transferable Availability Poisoning Attacks
by: Liu, Yiyong, et al.
Published: (2023)
by: Liu, Yiyong, et al.
Published: (2023)
DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models
by: Yuan, Haonan, et al.
Published: (2024)
by: Yuan, Haonan, et al.
Published: (2024)
Revealing the Challenges of Sim-to-Real Transfer in Model-Based Reinforcement Learning via Latent Space Modeling
by: Lin, Zhilin, et al.
Published: (2025)
by: Lin, Zhilin, et al.
Published: (2025)
Learning Continually by Spectral Regularization
by: Lewandowski, Alex, et al.
Published: (2024)
by: Lewandowski, Alex, et al.
Published: (2024)
Time-varying Factor Augmented Vector Autoregression with Grouped Sparse Autoencoder
by: Luo, Yiyong, et al.
Published: (2025)
by: Luo, Yiyong, et al.
Published: (2025)
ECAT: A Entire space Continual and Adaptive Transfer Learning Framework for Cross-Domain Recommendation
by: Hou, Chaoqun, et al.
Published: (2024)
by: Hou, Chaoqun, et al.
Published: (2024)
Efficient and Robust Regularized Federated Recommendation
by: Liu, Langming, et al.
Published: (2024)
by: Liu, Langming, et al.
Published: (2024)
DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
by: Li, Dongyuan, et al.
Published: (2024)
by: Li, Dongyuan, et al.
Published: (2024)
Hankel Singular Value Regularization for Highly Compressible State Space Models
by: Schwerdtner, Paul, et al.
Published: (2025)
by: Schwerdtner, Paul, et al.
Published: (2025)
A Study on Regularization-Based Continual Learning Methods for Indic ASR
by: T, Gokul Adethya, et al.
Published: (2025)
by: T, Gokul Adethya, et al.
Published: (2025)
Latent Spectral Regularization for Continual Learning
by: Frascaroli, Emanuele, et al.
Published: (2023)
by: Frascaroli, Emanuele, et al.
Published: (2023)
In-Context Learning for Pure Exploration in Continuous Spaces
by: Russo, Alessio, et al.
Published: (2026)
by: Russo, Alessio, et al.
Published: (2026)
Deep State-Space Generative Model For Correlated Time-to-Event Predictions
by: Xue, Yuan, et al.
Published: (2024)
by: Xue, Yuan, et al.
Published: (2024)
COPR: Continual Learning Human Preference through Optimal Policy Regularization
by: Zhang, Han, et al.
Published: (2023)
by: Zhang, Han, et al.
Published: (2023)
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces
by: Tiwari, Saket, et al.
Published: (2022)
by: Tiwari, Saket, et al.
Published: (2022)
Layer-Adaptive State Pruning for Deep State Space Models
by: Gwak, Minseon, et al.
Published: (2024)
by: Gwak, Minseon, et al.
Published: (2024)
Soft Diamond Regularizers for Deep Learning
by: Adigun, Olaoluwa, et al.
Published: (2024)
by: Adigun, Olaoluwa, et al.
Published: (2024)
Nuclear Norm Regularization for Deep Learning
by: Scarvelis, Christopher, et al.
Published: (2024)
by: Scarvelis, Christopher, et al.
Published: (2024)
Estimating Implicit Regularization in Deep Learning
by: Rudoler, Joseph H., et al.
Published: (2026)
by: Rudoler, Joseph H., et al.
Published: (2026)
Sparsified State-Space Models are Efficient Highway Networks
by: Song, Woomin, et al.
Published: (2025)
by: Song, Woomin, et al.
Published: (2025)
PPG-to-ECG Signal Translation for Continuous Atrial Fibrillation Detection via Attention-based Deep State-Space Modeling
by: Vo, Khuong, et al.
Published: (2023)
by: Vo, Khuong, et al.
Published: (2023)
Similar Items
-
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference
by: Lin, Zhidi, et al.
Published: (2023) -
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
by: Lin, Zhidi, et al.
Published: (2025) -
Hybrid Data-Driven SSM for Interpretable and Label-Free mmWave Channel Prediction
by: Sun, Yiyong, et al.
Published: (2024) -
Preventing Model Collapse in Gaussian Process Latent Variable Models
by: Li, Ying, et al.
Published: (2024) -
Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel
by: Suwandi, Richard Cornelius, et al.
Published: (2023)