Guardado en:
| Autores principales: | Biswas, Sani, Ansari, Khursheed J., Akhtar, Md. Nasim |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.02524 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Discovering intrinsic multi-compartment pharmacometric models using Physics Informed Neural Networks
por: Nasim, Imran, et al.
Publicado: (2024)
por: Nasim, Imran, et al.
Publicado: (2024)
Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control
por: Xiao, Maxiu, et al.
Publicado: (2025)
por: Xiao, Maxiu, et al.
Publicado: (2025)
Dynamic Reconstruction of Ultrasound-Derived Flow Fields With Physics-Informed Neural Fields
por: Patel, Viraj, et al.
Publicado: (2025)
por: Patel, Viraj, et al.
Publicado: (2025)
PIDM-DP: Physics-Informed Diffusion with Dormand-Prince Integration for Chaotic System Identification and State Reconstruction across Multiple Dynamical Regimes
por: Dabral, Shailendra
Publicado: (2026)
por: Dabral, Shailendra
Publicado: (2026)
Physics-Guided Concentration Inference from Resistance Transients in a Mixed-Phase SnO-SnO$_2$ Carbon Monoxide Sensor with p-n Switching
por: Biswas, Sani, et al.
Publicado: (2026)
por: Biswas, Sani, et al.
Publicado: (2026)
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks
por: Haywood-Alexander, Marcus, et al.
Publicado: (2024)
por: Haywood-Alexander, Marcus, et al.
Publicado: (2024)
A Comprehensive Review on Understanding the Decentralized and Collaborative Approach in Machine Learning
por: Saif, Sarwar, et al.
Publicado: (2025)
por: Saif, Sarwar, et al.
Publicado: (2025)
Non-Invasive Reconstruction of Cardiac Activation Dynamics Using Physics-Informed Neural Networks
por: Dermul, Nathan, et al.
Publicado: (2026)
por: Dermul, Nathan, et al.
Publicado: (2026)
Time-Scale Coupling Between States and Parameters in Recurrent Neural Networks
por: Livi, Lorenzo
Publicado: (2025)
por: Livi, Lorenzo
Publicado: (2025)
Physics-Informed Neural Networks for Vessel Trajectory Prediction: Learning Time-Discretized Kinematic Dynamics via Finite Differences
por: Alam, Md Mahbub, et al.
Publicado: (2025)
por: Alam, Md Mahbub, et al.
Publicado: (2025)
Parameter Identification for Partial Differential Equation with Jump Discontinuities in Coefficients by Markov Switching Model and Physics-Informed Machine Learning
por: Zhang, Zhikun, et al.
Publicado: (2025)
por: Zhang, Zhikun, et al.
Publicado: (2025)
Unsupervised Deep Clustering of MNIST with Triplet-Enhanced Convolutional Autoencoders
por: Ansari, Md. Faizul Islam
Publicado: (2025)
por: Ansari, Md. Faizul Islam
Publicado: (2025)
Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical Systems
por: Nasim, Imran, et al.
Publicado: (2024)
por: Nasim, Imran, et al.
Publicado: (2024)
Physics-Informed Graph Neural Networks for Transverse Momentum Estimation in CMS Trigger Systems
por: Jahin, Md Abrar, et al.
Publicado: (2025)
por: Jahin, Md Abrar, et al.
Publicado: (2025)
Novel Deep Learning Architecture for Heart Disease Prediction using Convolutional Neural Network
por: Hussain, Shadab, et al.
Publicado: (2021)
por: Hussain, Shadab, et al.
Publicado: (2021)
Robust Parameter and State Estimation in Multiscale Neuronal Systems Using Physics-Informed Neural Networks
por: Wei, Changliang, et al.
Publicado: (2026)
por: Wei, Changliang, et al.
Publicado: (2026)
Physics-Informed Neural Nets for Control of Dynamical Systems
por: Antonelo, Eric Aislan, et al.
Publicado: (2021)
por: Antonelo, Eric Aislan, et al.
Publicado: (2021)
Modeling COVID-19 Dynamics in German States Using Physics-Informed Neural Networks
por: Rothenbeck, Phillip, et al.
Publicado: (2025)
por: Rothenbeck, Phillip, et al.
Publicado: (2025)
Physics-Informed Neural Networks for Joint Source and Parameter Estimation in Advection-Diffusion Equations
por: Anague, Brenda, et al.
Publicado: (2025)
por: Anague, Brenda, et al.
Publicado: (2025)
BRAID: Input-Driven Nonlinear Dynamical Modeling of Neural-Behavioral Data
por: Vahidi, Parsa, et al.
Publicado: (2025)
por: Vahidi, Parsa, et al.
Publicado: (2025)
Vertical Symbolic Regression via Deep Policy Gradient
por: Jiang, Nan, et al.
Publicado: (2024)
por: Jiang, Nan, et al.
Publicado: (2024)
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
por: Jiang, Nan, et al.
Publicado: (2024)
por: Jiang, Nan, et al.
Publicado: (2024)
Dissipative Latent Residual Physics-Informed Neural Networks for Modeling and Identification of Electromechanical Systems
por: Long, Youyuan, et al.
Publicado: (2026)
por: Long, Youyuan, et al.
Publicado: (2026)
Learning Transferable Friction Models and LuGre Identification Via Physics-Informed Neural Networks
por: Ozmen, Asutay, et al.
Publicado: (2025)
por: Ozmen, Asutay, et al.
Publicado: (2025)
Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
por: Ganguly, Abhisek, et al.
Publicado: (2026)
por: Ganguly, Abhisek, et al.
Publicado: (2026)
Variational Physics-Informed Ansatz for Reconstructing Hidden Interaction Networks from Steady States
por: Luo, Kaiming
Publicado: (2025)
por: Luo, Kaiming
Publicado: (2025)
Principles and Components of Federated Learning Architectures
por: Nasim, MD Abdullah Al, et al.
Publicado: (2025)
por: Nasim, MD Abdullah Al, et al.
Publicado: (2025)
Physics-Informed Regression: Parameter Estimation in Parameter-Linear Nonlinear Dynamic Models
por: Nielsen, Jonas Søeborg, et al.
Publicado: (2025)
por: Nielsen, Jonas Søeborg, et al.
Publicado: (2025)
Automated Manifold Learning for Reduced Order Modeling
por: Nasim, Imran, et al.
Publicado: (2025)
por: Nasim, Imran, et al.
Publicado: (2025)
LeafLife: An Explainable Deep Learning Framework with Robustness for Grape Leaf Disease Recognition
por: Alam, B. M. Shahria, et al.
Publicado: (2026)
por: Alam, B. M. Shahria, et al.
Publicado: (2026)
On Tuning Neural ODE for Stability, Consistency and Faster Convergence
por: Akhtar, Sheikh Waqas
Publicado: (2023)
por: Akhtar, Sheikh Waqas
Publicado: (2023)
Replacing Tunable Parameters in Weather and Climate Models with State-Dependent Functions using Reinforcement Learning
por: Nath, Pritthijit, et al.
Publicado: (2026)
por: Nath, Pritthijit, et al.
Publicado: (2026)
CI-RKM: A Class-Informed Approach to Robust Restricted Kernel Machines
por: Mishra, Ritik, et al.
Publicado: (2025)
por: Mishra, Ritik, et al.
Publicado: (2025)
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
por: Chu, Mengyu, et al.
Publicado: (2022)
por: Chu, Mengyu, et al.
Publicado: (2022)
Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks
por: Song, Siyuan, et al.
Publicado: (2023)
por: Song, Siyuan, et al.
Publicado: (2023)
Learning Hybrid Dynamics Models With Simulator-Informed Latent States
por: Ensinger, Katharina, et al.
Publicado: (2023)
por: Ensinger, Katharina, et al.
Publicado: (2023)
Physics-Informed Neural Networks with Architectural Physics Embedding for Large-Scale Wave Field Reconstruction
por: Zhang, Huiwen, et al.
Publicado: (2026)
por: Zhang, Huiwen, et al.
Publicado: (2026)
Physics-Informed Neural ODEs with Scale-Aware Residuals for Learning Stiff Biophysical Dynamics
por: Kainth, Kamalpreet Singh, et al.
Publicado: (2025)
por: Kainth, Kamalpreet Singh, et al.
Publicado: (2025)
Inferring Cosmological Parameters with Evidential Physics-Informed Neural Networks
por: Tan, Hai Siong
Publicado: (2025)
por: Tan, Hai Siong
Publicado: (2025)
Quantum-Informed Contrastive Learning with Dynamic Mixup Augmentation for Class-Imbalanced Expert Systems
por: Jahin, Md Abrar, et al.
Publicado: (2025)
por: Jahin, Md Abrar, et al.
Publicado: (2025)
Ejemplares similares
-
Discovering intrinsic multi-compartment pharmacometric models using Physics Informed Neural Networks
por: Nasim, Imran, et al.
Publicado: (2024) -
Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control
por: Xiao, Maxiu, et al.
Publicado: (2025) -
Dynamic Reconstruction of Ultrasound-Derived Flow Fields With Physics-Informed Neural Fields
por: Patel, Viraj, et al.
Publicado: (2025) -
PIDM-DP: Physics-Informed Diffusion with Dormand-Prince Integration for Chaotic System Identification and State Reconstruction across Multiple Dynamical Regimes
por: Dabral, Shailendra
Publicado: (2026) -
Physics-Guided Concentration Inference from Resistance Transients in a Mixed-Phase SnO-SnO$_2$ Carbon Monoxide Sensor with p-n Switching
por: Biswas, Sani, et al.
Publicado: (2026)