Copertina

A Physics Informed Machine Learning Framework for Optimal Sensor Placement and Parameter Estimation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Venianakis, Georgios, Theodoropoulos, Constantinos, Kavousanakis, Michail
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach
di: Fabiani, Gianluca, et al.
Pubblicazione: (2026)

Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks
di: Li, Sirui, et al.
Pubblicazione: (2025)

Towards A Flexible Accuracy-Oriented Deep Learning Module Inference Latency Prediction Framework for Adaptive Optimization Algorithms
di: Shen, Jingran, et al.
Pubblicazione: (2023)

Time-Vertex Machine Learning for Optimal Sensor Placement in Temporal Graph Signals: Applications in Structural Health Monitoring
di: Niresi, Keivan Faghih, et al.
Pubblicazione: (2025)

Deep Optimal Sensor Placement for Black Box Stochastic Simulations
di: Cordero-Encinar, Paula, et al.
Pubblicazione: (2024)

Physics-Informed Machine Learning for Pouch Cell Temperature Estimation
di: Liu, Zheng
Pubblicazione: (2026)

A Rapid Physics-Informed Machine Learning Framework Based on Extreme Learning Machine for Inverse Stefan Problems
di: Zhuang, Pei-Zhi, et al.
Pubblicazione: (2025)

Graph Neural Networks and Reinforcement Learning for Proactive Application Image Placement
di: Makris, Antonios, et al.
Pubblicazione: (2024)

PIGPVAE: Physics-Informed Gaussian Process Variational Autoencoders
di: Spitieris, Michail, et al.
Pubblicazione: (2025)

Sensor Placement for Urban Traffic Interpolation: A Data-Driven Evaluation to Inform Policy
di: Kaiser, Silke K.
Pubblicazione: (2026)

Towards Optimal Adapter Placement for Efficient Transfer Learning
di: Nowak, Aleksandra I., et al.
Pubblicazione: (2024)

Enhancing Strawberry Yield Forecasting with Backcasted IoT Sensor Data and Machine Learning
di: Ayall, Tewodros Alemu, et al.
Pubblicazione: (2025)

A Physics-Informed Learning Framework to Solve the Infinite-Horizon Optimal Control Problem
di: Fotiadis, Filippos, et al.
Pubblicazione: (2025)

Flow Field Reconstruction via Voronoi-Enhanced Physics-Informed Neural Networks with End-to-End Sensor Placement Optimization
di: Xiao, Renjie, et al.
Pubblicazione: (2026)

Physics-Informed Neural Networks for Joint Source and Parameter Estimation in Advection-Diffusion Equations
di: Anague, Brenda, et al.
Pubblicazione: (2025)

Sensor Placement for Learning in Flow Networks
di: Burudgunte, Arnav, et al.
Pubblicazione: (2023)

Parameter Identification for Partial Differential Equation with Jump Discontinuities in Coefficients by Markov Switching Model and Physics-Informed Machine Learning
di: Zhang, Zhikun, et al.
Pubblicazione: (2025)

SPINN: An Optimal Self-Supervised Physics-Informed Neural Network Framework
di: Pirayeshshirazinezhad, Reza
Pubblicazione: (2025)

Physics-Informed Machine Learning On Polar Ice: A Survey
di: Liu, Zesheng, et al.
Pubblicazione: (2024)

Transformer-Based Approach to Optimal Sensor Placement for Structural Health Monitoring of Probe Cards
di: Bejani, Mehdi, et al.
Pubblicazione: (2025)

Going with the Flow: Solving for Symmetry-Driven PDE dynamics with Physics-informed Neural Networks
di: Kavousanakis, Michail, et al.
Pubblicazione: (2025)

IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture
di: Ramani, Varun, et al.
Pubblicazione: (2024)

Communication-Efficient Distributed Deep Learning via Federated Dynamic Averaging
di: Theologitis, Michail, et al.
Pubblicazione: (2024)

A Study on Stabilizer Rényi Entropy Estimation using Machine Learning
di: Lipardi, Vincenzo, et al.
Pubblicazione: (2025)

Estimating Ising Models in Total Variation Distance
di: Daskalakis, Constantinos, et al.
Pubblicazione: (2025)

Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning
di: Daniels, Mara, et al.
Pubblicazione: (2025)

ActivePusher: Active Learning and Planning with Residual Physics for Nonprehensile Manipulation
di: Zhong, Zhuoyun, et al.
Pubblicazione: (2025)

PIDT: Physics-Informed Digital Twin for Optical Fiber Parameter Estimation
di: Jiang, Zicong, et al.
Pubblicazione: (2026)

Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks
di: Koumpanakis, Michail, et al.
Pubblicazione: (2024)

Learning to Optimise Climate Sensor Placement using a Transformer
di: Wang, Chen, et al.
Pubblicazione: (2023)

A Machine Learning-Based Multimodal Framework for Wearable Sensor-Based Archery Action Recognition and Stress Estimation
di: Liu, Xianghe, et al.
Pubblicazione: (2025)

A Hybrid Surrogate for Electric Vehicle Parameter Estimation and Power Consumption via Physics-Informed Neural Operators
di: Lim, Hansol, et al.
Pubblicazione: (2025)

Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement
di: Jin, Hongwei, et al.
Pubblicazione: (2024)

A PAC-Bayesian View of Generalisation for Physics-Informed Machine Learning
di: Nguyen, Thien V., et al.
Pubblicazione: (2026)

Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning
di: Patsatzis, Dimitrios G., et al.
Pubblicazione: (2023)

Maturity Framework for Enhancing Machine Learning Quality
di: Castelli, Angelantonio, et al.
Pubblicazione: (2025)

Physics-Informed Regression: Parameter Estimation in Parameter-Linear Nonlinear Dynamic Models
di: Nielsen, Jonas Søeborg, et al.
Pubblicazione: (2025)

Ga$_2$O$_3$ TCAD Mobility Parameter Calibration using Simulation Augmented Machine Learning with Physics Informed Neural Network
di: Nguyen, Le Minh Long, et al.
Pubblicazione: (2025)

Physics-Informed Reward Machines
di: Ajeleye, Daniel, et al.
Pubblicazione: (2025)

Placeit! A Framework for Learning Robot Object Placement Skills
di: Ferrad, Amina, et al.
Pubblicazione: (2025)