Saved in:
| Main Authors: | Padhy, Apurba Prasad, Camacho, Fernando, Mukhopadhyay, Saibal |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.00534 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Layer-Adaptive State Pruning for Deep State Space Models
by: Gwak, Minseon, et al.
Published: (2024)
by: Gwak, Minseon, et al.
Published: (2024)
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs
by: Saha, Priyabrata, et al.
Published: (2024)
by: Saha, Priyabrata, et al.
Published: (2024)
RoboKoop: Efficient Control Conditioned Representations from Visual Input in Robotics using Koopman Operator
by: Kumawat, Hemant, et al.
Published: (2024)
by: Kumawat, Hemant, et al.
Published: (2024)
Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
by: Kang, Beomseok, et al.
Published: (2024)
by: Kang, Beomseok, et al.
Published: (2024)
Koopman Subspace Pruning in Reproducing Kernel Hilbert Spaces via Principal Vectors
by: Shah, Dhruv, et al.
Published: (2026)
by: Shah, Dhruv, et al.
Published: (2026)
Dictionary-Learning-Based Data Pruning for System Identification
by: Wang, Tingna, et al.
Published: (2025)
by: Wang, Tingna, et al.
Published: (2025)
State-Free Inference of State-Space Models: The Transfer Function Approach
by: Parnichkun, Rom N., et al.
Published: (2024)
by: Parnichkun, Rom N., et al.
Published: (2024)
Recursive Gaussian Process State Space Model
by: Zheng, Tengjie, et al.
Published: (2024)
by: Zheng, Tengjie, et al.
Published: (2024)
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)
Adversarial Robustness of Deep State Space Models for Forecasting
by: Anand, Sribalaji C., et al.
Published: (2026)
by: Anand, Sribalaji C., et al.
Published: (2026)
FLAMES: A Hybrid Spiking-State Space Model for Adaptive Memory Retention in Event-Based Learning
by: Chakraborty, Biswadeep, et al.
Published: (2025)
by: Chakraborty, Biswadeep, et al.
Published: (2025)
Learning Surrogate LPV State-Space Models with Uncertainty Quantification
by: Olucha, E. Javier, et al.
Published: (2026)
by: Olucha, E. Javier, et al.
Published: (2026)
Geometric SSM: LTI State Space Models for Selective Tasks
by: Casti, Umberto, et al.
Published: (2025)
by: Casti, Umberto, et al.
Published: (2025)
Systolic Array-based Accelerator for Structured State-Space Models
by: Raja, Shiva, et al.
Published: (2025)
by: Raja, Shiva, et al.
Published: (2025)
Component-Aware Pruning Framework for Neural Network Controllers via Gradient-Based Importance Estimation
by: Sundaram, Ganesh, et al.
Published: (2026)
by: Sundaram, Ganesh, et al.
Published: (2026)
Time-Varying Deep State Space Models for Sequences with Switching Dynamics
by: Karilanova, Sanja, et al.
Published: (2026)
by: Karilanova, Sanja, et al.
Published: (2026)
Learning Stable and Robust Linear Parameter-Varying State-Space Models
by: Verhoek, Chris, et al.
Published: (2023)
by: Verhoek, Chris, et al.
Published: (2023)
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024)
by: Chakraborty, Biswadeep, et al.
Published: (2024)
Sparse Mamba: Introducing Controllability, Observability, And Stability To Structural State Space Models
by: Hamdan, Emadeldeen, et al.
Published: (2024)
by: Hamdan, Emadeldeen, et al.
Published: (2024)
Naga: Vedic Encoding for Deep State Space Models
by: Schaller, Melanie, et al.
Published: (2025)
by: Schaller, Melanie, 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)
by: Zheng, Tengjie, 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)
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)
by: Sakamoto, Hiroki, et al.
Published: (2025)
L2RU: a Structured State Space Model with prescribed L2-bound
by: Massai, Leonardo, et al.
Published: (2025)
by: Massai, Leonardo, et al.
Published: (2025)
State Space Models as Foundation Models: A Control Theoretic Overview
by: Alonso, Carmen Amo, et al.
Published: (2024)
by: Alonso, Carmen Amo, et al.
Published: (2024)
State-Space Kolmogorov Arnold Networks for Interpretable Nonlinear System Identification
by: Cruz, Gonçalo Granjal, et al.
Published: (2025)
by: Cruz, Gonçalo Granjal, et al.
Published: (2025)
Centrality-Based Pruning for Efficient Echo State Networks
by: Laudari, Sudip
Published: (2026)
by: Laudari, Sudip
Published: (2026)
Predictability Enables Parallelization of Nonlinear State Space Models
by: Gonzalez, Xavier, et al.
Published: (2025)
by: Gonzalez, Xavier, et al.
Published: (2025)
Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
by: Mohamed, Nazal, et al.
Published: (2026)
by: Mohamed, Nazal, et al.
Published: (2026)
Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity
by: Pervej, Md Ferdous, et al.
Published: (2023)
by: Pervej, Md Ferdous, et al.
Published: (2023)
PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power Systems
by: Menati, Ali, et al.
Published: (2024)
by: Menati, Ali, et al.
Published: (2024)
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
by: Sieber, Jerome, et al.
Published: (2024)
by: Sieber, Jerome, et al.
Published: (2024)
Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
by: Adler, Saghar, et al.
Published: (2023)
by: Adler, Saghar, et al.
Published: (2023)
Stable-by-Design Neural Network-Based LPV State-Space Models for System Identification
by: Sertbaş, Ahmet Eren, et al.
Published: (2025)
by: Sertbaş, Ahmet Eren, et al.
Published: (2025)
On the Relation of State Space Models and Hidden Markov Models
by: Ghojogh, Aydin, et al.
Published: (2026)
by: Ghojogh, Aydin, et al.
Published: (2026)
Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)
Beyond Weather Correlation: A Comparative Study of Static and Temporal Neural Architectures for Fine-Grained Residential Energy Consumption Forecasting in Melbourne, Australia
by: Hewage, Prasad Nimantha Madusanka Ukwatta, et al.
Published: (2026)
by: Hewage, Prasad Nimantha Madusanka Ukwatta, et al.
Published: (2026)
Characterizing State Space Model and Hybrid Language Model Performance with Long Context
by: Mitra, Saptarshi, et al.
Published: (2025)
by: Mitra, Saptarshi, et al.
Published: (2025)
Controller Design for Structured State-space Models via Contraction Theory
by: Zakwan, Muhammad, et al.
Published: (2026)
by: Zakwan, Muhammad, et al.
Published: (2026)
PACE: Prune-And-Compress Ensemble Models
by: Akkerman, Fabian, et al.
Published: (2026)
by: Akkerman, Fabian, et al.
Published: (2026)
Similar Items
-
Layer-Adaptive State Pruning for Deep State Space Models
by: Gwak, Minseon, et al.
Published: (2024) -
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs
by: Saha, Priyabrata, et al.
Published: (2024) -
RoboKoop: Efficient Control Conditioned Representations from Visual Input in Robotics using Koopman Operator
by: Kumawat, Hemant, et al.
Published: (2024) -
Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
by: Kang, Beomseok, et al.
Published: (2024) -
Koopman Subspace Pruning in Reproducing Kernel Hilbert Spaces via Principal Vectors
by: Shah, Dhruv, et al.
Published: (2026)