:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Padhy, Apurba Prasad, Camacho, Fernando, Mukhopadhyay, Saibal
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Systems and Control
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)

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)

Dictionary-Learning-Based Data Pruning for System Identification
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)

Recursive Gaussian Process State Space Model
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)

Adversarial Robustness of Deep State Space Models for Forecasting
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)

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)

Component-Aware Pruning Framework for Neural Network Controllers via Gradient-Based Importance Estimation
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)

Learning Stable and Robust Linear Parameter-Varying State-Space Models
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)

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

Naga: Vedic Encoding for Deep State Space Models
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)

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)

L2RU: a Structured State Space Model with prescribed L2-bound
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)

State-Space Kolmogorov Arnold Networks for Interpretable Nonlinear System Identification
by: Cruz, Gonçalo Granjal, et al.
Published: (2025)

Centrality-Based Pruning for Efficient Echo State Networks
by: Laudari, Sudip
Published: (2026)

Predictability Enables Parallelization of Nonlinear State Space Models
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)

Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity
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)

Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
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)

Stable-by-Design Neural Network-Based LPV State-Space Models for System Identification
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)

Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems
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)

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

Controller Design for Structured State-space Models via Contraction Theory
by: Zakwan, Muhammad, et al.
Published: (2026)

PACE: Prune-And-Compress Ensemble Models
by: Akkerman, Fabian, et al.
Published: (2026)