Cover Image

Time-Varying Deep State Space Models for Sequences with Switching Dynamics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Karilanova, Sanja, Dey, Subhrakanti, Özçelikkale, Ayça
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Delays in Spiking Neural Networks: A State Space Model Approach
by: Karilanova, Sanja, et al.
Published: (2025)

State-Space Model Inspired Multiple-Input Multiple-Output Spiking Neurons
by: Karilanova, Sanja, et al.
Published: (2025)

Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions
by: Karilanova, Sanja, et al.
Published: (2026)

Low-Bit Data Processing Using Multiple-Output Spiking Neurons with Non-linear Reset Feedback
by: Karilanova, Sanja, et al.
Published: (2025)

Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks
by: Karilanova, Sanja, et al.
Published: (2024)

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

T2S-MPC: Time-Embedded Online Adaptive Model Predictive Control for Time-Varying Dynamics
by: Shen, Zeyu, et al.
Published: (2026)

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

Model-free LQG Control with Chance Constraints
by: Naha, Arunava, et al.
Published: (2026)

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

Policy Gradient-based Model Free Optimal LQG Control with a Probabilistic Risk Constraint
by: Naha, Arunava, et al.
Published: (2024)

PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power Systems
by: Menati, Ali, et al.
Published: (2024)

Improved Robustness of Deep Reinforcement Learning for Control of Time-Varying Systems by Bounded Extremum Seeking
by: Saxena, Shaifalee, et al.
Published: (2025)

Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective
by: Remman, Sindre Benjamin, et al.
Published: (2024)

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)

Naga: Vedic Encoding for Deep State Space Models
by: Schaller, Melanie, et al.
Published: (2025)

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

State Derivative Normalization for Continuous-Time Deep Neural Networks
by: Weigand, Jonas, et al.
Published: (2024)

Recursive Gaussian Process State Space Model
by: Zheng, Tengjie, et al.
Published: (2024)

Decentralized Online Regularized Learning Over Random Time-Varying Graphs
by: Zhang, Xiwei, et al.
Published: (2022)

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

Synthetic Data Generation for Minimum-Exposure Navigation in a Time-Varying Environment using Generative AI Models
by: Bapat, Nachiket U., et al.
Published: (2025)

Learning Exactly Linearizable Deep Dynamics Models
by: Moriyasu, Ryuta, et al.
Published: (2023)

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

Learning Surrogate LPV State-Space Models with Uncertainty Quantification
by: Olucha, E. Javier, 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)

Identifying Large-Scale Linear Parameter Varying Systems with Dynamic Mode Decomposition Methods
by: Jordanou, Jean Panaioti, et al.
Published: (2025)

Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics
by: Moroncelli, Angelo, et al.
Published: (2026)

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

Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation
by: Azimian, Behrouz, et al.
Published: (2023)

An Adaptive Grasping Force Tracking Strategy for Nonlinear and Time-Varying Object Behaviors
by: Cheng, Ziyang, et al.
Published: (2024)

On Convergence Analysis of Network-GIANT: An approximate Hessian-based fully distributed optimization algorithm
by: Das, Souvik, et al.
Published: (2026)

Multi-Target Radar Search and Track Using Sequence-Capable Deep Reinforcement Learning
by: Ewers, Jan-Hendrik, et al.
Published: (2025)

Modeling and Control of Deep Sign-Definite Dynamics with Application to Hybrid Powertrain Control
by: Kato, Teruki, et al.
Published: (2025)

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

L2RU: a Structured State Space Model with prescribed L2-bound
by: Massai, Leonardo, et al.
Published: (2025)

Predictor-Based Output-Feedback Control of Linear Systems with Time-Varying Input and Measurement Delays via Neural-Approximated Prediction Horizons
by: Bhan, Luke, et al.
Published: (2026)

Real-Time Risky Fault-Chain Search using Time-Varying Graph RNNs
by: Dwivedi, Anmol, et al.
Published: (2025)