:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zheng, Tengjie, Chen, Haipeng, Cheng, Lin, Gong, Shengping, Huang, Xu
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Systems and Control
Online Access:	https://arxiv.org/abs/2411.14679
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Recursive Inference for Heterogeneous Multi-Output GP State-Space Models with Arbitrary Moment Matching
by: Zheng, Tengjie, et al.
Published: (2025)

Sparse Kalman Identification for Partially Observable Systems via Adaptive Bayesian Learning
by: Mei, Jilan, et al.
Published: (2025)

Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression
by: Wang, Han, et al.
Published: (2025)

Physics-informed Gaussian Processes as Linear Model Predictive Controller
by: Tebbe, Jörn, et al.
Published: (2024)

Layer-Adaptive State Pruning for Deep State Space Models
by: Gwak, Minseon, et al.
Published: (2024)

Koopman-Equivariant Gaussian Processes
by: Bevanda, Petar, et al.
Published: (2025)

Space-Filling Regularization for Robust and Interpretable Nonlinear State Space Models
by: Klein, Hermann, et al.
Published: (2025)

Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
by: Adler, Saghar, et al.
Published: (2023)

State-Free Inference of State-Space Models: The Transfer Function Approach
by: Parnichkun, Rom N., et al.
Published: (2024)

Polynomial Chaos Expanded Gaussian Process
by: Polke, Dominik, et al.
Published: (2024)

Adversarial Robustness of Deep State Space Models for Forecasting
by: Anand, Sribalaji C., et al.
Published: (2026)

Streaming Generated Gaussian Process Experts for Online Learning and Control: Extended Version
by: Yang, Zewen, et al.
Published: (2025)

Stability Enhanced Gaussian Process Variational Autoencoders
by: Richardson, Carl R., et al.
Published: (2026)

AIRE-Prune: Asymptotic Impulse-Response Energy for State Pruning in State Space Models
by: Padhy, Apurba Prasad, et al.
Published: (2026)

Geometric SSM: LTI State Space Models for Selective Tasks
by: Casti, Umberto, et al.
Published: (2025)

Systolic Array-based Accelerator for Structured State-Space Models
by: Raja, Shiva, et al.
Published: (2025)

Learning Surrogate LPV State-Space Models with Uncertainty Quantification
by: Olucha, E. Javier, et al.
Published: (2026)

Machine Learning Detection of Lithium Plating in Lithium-ion Cells: A Gaussian Process Approach
by: Patnaik, Ayush, et al.
Published: (2025)

Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
by: Hsin, Junette, et al.
Published: (2023)

Steady-State Error Compensation for Reinforcement Learning with Quadratic Rewards
by: Wang, Liyao, et al.
Published: (2024)

Time-Varying Deep State Space Models for Sequences with Switching Dynamics
by: Karilanova, Sanja, et al.
Published: (2026)

Learning Stable and Robust Linear Parameter-Varying State-Space Models
by: Verhoek, Chris, et al.
Published: (2023)

Characterizing State Space Model and Hybrid Language Model Performance with Long Context
by: Mitra, Saptarshi, et al.
Published: (2025)

Real-Time Adaptive Safety-Critical Control with Gaussian Processes in High-Order Uncertain Models
by: Zhang, Yu, et al.
Published: (2024)

A Tutorial on Gaussian Process Learning-based Model Predictive Control
by: Wang, Jie, et al.
Published: (2024)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
by: Prajapat, Manish, et al.
Published: (2025)

Decentralized Event-Triggered Online Learning for Safe Consensus of Multi-Agent Systems with Gaussian Process Regression
by: Dai, Xiaobing, et al.
Published: (2024)

Sparse Mamba: Introducing Controllability, Observability, And Stability To Structural State Space Models
by: Hamdan, Emadeldeen, et al.
Published: (2024)

Cooperative Learning with Gaussian Processes for Euler-Lagrange Systems Tracking Control under Switching Topologies
by: Yang, Zewen, et al.
Published: (2024)

Recursively Feasible Probabilistic Safe Online Learning with Control Barrier Functions
by: Castañeda, Fernando, et al.
Published: (2022)

Learning-Based Stable Optimal Control for Infinite-Time Nonlinear Regulation Problems
by: Wang, Han, et al.
Published: (2025)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
by: Lederer, Armin, et al.
Published: (2019)

Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
by: Ewering, Jan-Hendrik, et al.
Published: (2025)

Power Flow Approximations for Multiphase Distribution Networks using Gaussian Processes
by: Glover, Daniel, et al.
Published: (2025)

Modeling Epidemic Spread: A Gaussian Process Regression Approach
by: She, Baike, et al.
Published: (2023)

Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network
by: Liu, Xu, et al.
Published: (2022)

Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees
by: de Jong, Thomas, et al.
Published: (2024)

Randomized Space-Time Sampling for Affine Graph Dynamical Systems
by: Gong, Le, et al.
Published: (2025)

Compression Method for Deep Diagonal State Space Model Based on $H^2$ Optimal Reduction
by: Sakamoto, Hiroki, et al.
Published: (2025)

A Deep State-Space Model Compression Method using Upper Bound on Output Error
by: Sakamoto, Hiroki, et al.
Published: (2025)