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A dynamical system is observable if there is a one-to-one mapping from the system's measured outputs and inputs to all of the system's states. Analytical and empirical tools exist for quantifying the (full state) observability of linear and…

Systems and Control · Electrical Eng. & Systems 2023-09-15 Benjamin Cellini , Burak Boyacıoğlu , Floris van Breugel

A large variety of dynamical systems, such as chemical and biomolecular systems, can be seen as networks of nonlinear entities. Prediction, control, and identification of such nonlinear networks require knowledge of the state of the system.…

Optimization and Control · Mathematics 2018-06-27 Aleksandar Haber , Ferenc Molnar , Adilson E. Motter

In multiagent systems (MASs), agents' observation upon system behaviours may improve the overall team performance, but may also leak sensitive information to an observer. A quantified observability analysis can thus be useful to assist…

Artificial Intelligence · Computer Science 2023-10-05 Chunyan Mu , Jun Pang

Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself constitutes an informative process. When using such data to…

Machine Learning · Computer Science 2022-05-27 Vincent Jeanselme , Glen Martin , Niels Peek , Matthew Sperrin , Brian Tom , Jessica Barrett

The advent of large-scale neural recordings has enabled new methods to discover the computational mechanisms of neural circuits by understanding the rules that govern how their state evolves over time. While these \textit{neural dynamics}…

Neurons and Cognition · Quantitative Biology 2023-09-13 Christopher Versteeg , Andrew R. Sedler , Jonathan D. McCart , Chethan Pandarinath

We study the problem of performance optimization of closed-loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed-loop performance by automatically tuning…

Machine Learning · Computer Science 2023-01-31 Wenjie Xu , Colin N Jones , Bratislav Svetozarevic , Christopher R. Laughman , Ankush Chakrabarty

We propose a novel performance metric for articulated robots with distributed directional sensors called the sensor observability analysis (SOA). These robot-mounted distributed directional sensors (e.g., joint torque sensors) change their…

Robotics · Computer Science 2024-05-31 Christopher Yee Wong , Wael Suleiman

End-to-end learning of dynamical systems with black-box models, such as neural ordinary differential equations (ODEs), provides a flexible framework for learning dynamics from data without prescribing a mathematical model for the dynamics.…

Machine Learning · Statistics 2022-06-20 Paidamoyo Chapfuwa , Sherri Rose , Lawrence Carin , Edward Meeds , Ricardo Henao

Vision-Language-Action (VLA) models have recently enabled embodied agents to perform increasingly complex tasks by jointly reasoning over visual, linguistic, and motor modalities. However, we find that the prevailing notion of…

Machine Learning · Computer Science 2026-03-20 Zhuofan Li , Hongkun Yang , Zhenyang Chen , Yangxuan Chen , Yingyan , Lin , Chaojian Li

Vision-Language-Action Models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that of Large Language Models (LLMs), VLAs exhibit higher complexity due to their multi-modal…

Robotics · Computer Science 2026-03-06 Hugo Buurmeijer , Carmen Amo Alonso , Aiden Swann , Marco Pavone

This paper proposes a novel approach for designing functional observers for nonlinear systems, with linear error dynamics and assignable poles. Sufficient conditions for functional observability are first derived, leading to functional…

Systems and Control · Electrical Eng. & Systems 2025-01-03 Costas Kravaris

The internal state of a dynamical system, a set of variables that defines its evolving configuration, is often hidden and cannot be fully measured, posing a central challenge for real-time monitoring and control. While observers are…

Systems and Control · Electrical Eng. & Systems 2025-12-09 Yuan Zhang , Ziyuan Luo , Wenxuan Xu , Jiayu Wu , Wenqi Cao , Ranbo Cheng , Tingting Qin , Yuanqing Xia , Mohamed Darouach , Aming Li , Tyrone Fernando

Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and…

Systems and Control · Electrical Eng. & Systems 2021-04-15 Shweta Dahale , Balasubramaniam Natarajan

Observability is the property that enables to distinguish two different locations in $n$-dimensional state space from a reduced number of measured variables, usually just one. In high-dimensional systems it is therefore important to make…

Neurons and Cognition · Quantitative Biology 2019-05-06 Luis A. Aguirre , Leonardo L. Portes , Christophe Letellier

When complex systems with nonlinear dynamics achieve an output performance objective, only a fraction of the state dynamics significantly impacts that output. Those minimal state dynamics can be identified using the differential geometric…

Optimization and Control · Mathematics 2022-10-19 Shara Balakrishnan , Aqib Hasnain , Robert Egbert , Enoch Yeung

This paper investigates the online estimation of neural activity within the primary visual cortex (V1) in the framework of observability theory. We focus on a low-dimensional neural fields modeling hypercolumnar activity to describe…

Optimization and Control · Mathematics 2024-03-05 Adel Malik Annabi , Dario Prandi , Jean-Baptiste Pomet , Ludovic Sacchelli

Non-Markovian effects in an open-system dynamics are usually associated to information backflows from the environment to the system. However, the way these backflows manifest and how to detect them is unclear. A natural approach is to study…

Quantum Physics · Physics 2020-07-22 Dario De Santis , Markus Johansson , Bogna Bylicka , Nadja K. Bernardes , Antonio Acín

Video-based Clinical Gait Analysis often suffers from poor generalization as models overfit environmental biases instead of capturing pathological motion. To address this, we propose BioGait-VLM, a tri-modal Vision-Language-Biomechanics…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Erdong Chen , Yuyang Ji , Jacob K. Greenberg , Benjamin Steel , Faraz Arkam , Abigail Lewis , Pranay Singh , Feng Liu

In robotics, structural design and behavior optimization have long been considered separate processes, resulting in the development of systems with limited capabilities. Recently, co-design methods have gained popularity, where bi-level…

Robotics · Computer Science 2025-07-02 Rohit Kumar , Melya Boukheddimi , Dennis Mronga , Shivesh Kumar , Frank Kirchner

Inventory-policy comparisons are often difficult to interpret because performance depends on the evaluation contract as much as on the policy itself. Differences in topology, demand regime, information access, feasibility constraints,…

Machine Learning · Computer Science 2026-05-13 Reza Barati , Qinmin Vivian Hu