Saved in:
| Main Authors: | Lucas Tesán, González, David, Martins, Pedro, Cueto, Elías |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2026
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.18958411 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Thermodynamics-informed graph neural networks for real-time simulation of digital human twins
by: Tesán, Lucas, et al.
Published: (2024)
by: Tesán, Lucas, et al.
Published: (2024)
On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition
by: Tesan, Lucas, et al.
Published: (2025)
by: Tesan, Lucas, et al.
Published: (2025)
Graph neural networks informed locally by thermodynamics
by: Tierz, Alicia, et al.
Published: (2024)
by: Tierz, Alicia, et al.
Published: (2024)
Preprint, models and results: Biologically informed neural network models are robust to spurious interactions via self-pruning
by: Nordenstorm, Olof
Published: (2025)
by: Nordenstorm, Olof
Published: (2025)
The impact of neural network optimization on real-time cloud decision systems
by: Priya Narayanan
Published: (2025)
by: Priya Narayanan
Published: (2025)
Thermodynamics-informed super-resolution of scarce temporal dynamics data
by: Bermejo-Barbanoj, Carlos, et al.
Published: (2024)
by: Bermejo-Barbanoj, Carlos, et al.
Published: (2024)
Is uniform expressivity too restrictive? Towards efficient expressivity of graph neural networks
by: Khalife, Sammy, et al.
Published: (2024)
by: Khalife, Sammy, et al.
Published: (2024)
A comparison of Single- and Double-generator formalisms for Thermodynamics-Informed Neural Networks
by: Urdeitx, Pau, et al.
Published: (2024)
by: Urdeitx, Pau, et al.
Published: (2024)
Data for the study: "Force and stress calculations with a neural-network wave function for solids"
by: Qian, Yubing
Published: (2024)
by: Qian, Yubing
Published: (2024)
Efficient n-body simulations using physics informed graph neural networks
by: Ramos-Osuna, Víctor, et al.
Published: (2025)
by: Ramos-Osuna, Víctor, et al.
Published: (2025)
Real‐time monitoring of tunnel structures using digital twin and artificial intelligence: A short overview
by: Mohammad Afrazi, et al.
Published: (2025)
by: Mohammad Afrazi, et al.
Published: (2025)
A domain adaptation neural network for digital twin-supported fault diagnosis
by: Chen, Zhenling, et al.
Published: (2025)
by: Chen, Zhenling, et al.
Published: (2025)
Bayesian dynamic mode decomposition for real-time ship motion digital twinning
by: Palma, Giorgio, et al.
Published: (2024)
by: Palma, Giorgio, et al.
Published: (2024)
SaeGraphDTI: drug-target interaction prediction based on sequence attribute extraction and graph neural network.
by: Zhang, Qiaosheng, et al.
Published: (2025)
by: Zhang, Qiaosheng, et al.
Published: (2025)
The twin peaks of learning neural networks
by: Demyanenko, Elizaveta, et al.
Published: (2024)
by: Demyanenko, Elizaveta, et al.
Published: (2024)
Variational Graph Neural Networks for Uncertainty Quantification in Inverse Problems
by: Gonzalez, David, et al.
Published: (2026)
by: Gonzalez, David, et al.
Published: (2026)
Cost-informed dimensionality reduction for structural digital twin technologies
by: Hughes, Aidan J., et al.
Published: (2024)
by: Hughes, Aidan J., et al.
Published: (2024)
Leveraging chaotic transients in the training of artificial neural networks
by: Jiménez-González, Pedro, et al.
Published: (2025)
by: Jiménez-González, Pedro, et al.
Published: (2025)
Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages
by: Katsidoniotaki, Eirini, et al.
Published: (2024)
by: Katsidoniotaki, Eirini, et al.
Published: (2024)
Contextual Interpretation: An Adaptive Framework for Situated reference resolution
by: Kaliappan, Velu
Published: (2025)
by: Kaliappan, Velu
Published: (2025)
MeshGraphNet-Transformer: Scalable Mesh-based Learned Simulation for Solid Mechanics
by: Iparraguirre, Mikel M., et al.
Published: (2026)
by: Iparraguirre, Mikel M., et al.
Published: (2026)
Grey-informed neural network for time-series forecasting
by: Xie, Wanli, et al.
Published: (2024)
by: Xie, Wanli, et al.
Published: (2024)
Detecting Cybersecurity Threats using Deep Learning
by: Ali, Ratul
Published: (2025)
by: Ali, Ratul
Published: (2025)
Particle-based plasma simulation using a graph neural network
by: Mlinarević, Marin, et al.
Published: (2025)
by: Mlinarević, Marin, et al.
Published: (2025)
Optimal time sampling in physics-informed neural networks
by: Turinici, Gabriel
Published: (2024)
by: Turinici, Gabriel
Published: (2024)
Deep Learning-Based Analysis of Precipitation Blocking at the Northwestern Iran Border with Comparative Insights from Utah, USA
by: Sohrabi, Mohammad
Published: (2025)
by: Sohrabi, Mohammad
Published: (2025)
Physics-informed graph neural networks for flow field estimation in carotid arteries
by: Suk, Julian, et al.
Published: (2024)
by: Suk, Julian, et al.
Published: (2024)
Improved generalization with deep neural operators for engineering systems: Path towards digital twin
by: Kobayashi, Kazuma, et al.
Published: (2023)
by: Kobayashi, Kazuma, et al.
Published: (2023)
Inverse analysis of granular flows using differentiable graph neural network simulator
by: Choi, Yongjin, et al.
Published: (2024)
by: Choi, Yongjin, et al.
Published: (2024)
Kolmogorov-Arnold graph neural networks for chemically informed prediction tasks on inorganic nanomaterials
by: Volzhin, Nikita, et al.
Published: (2025)
by: Volzhin, Nikita, et al.
Published: (2025)
Distill n' Explain: explaining graph neural networks using simple surrogates
by: Pereira, Tamara, et al.
Published: (2023)
by: Pereira, Tamara, et al.
Published: (2023)
The logic of rational graph neural networks
by: Khalife, Sammy
Published: (2023)
by: Khalife, Sammy
Published: (2023)
Physics-informed self-supervised learning for predictive modeling of coronary artery digital twins
by: Sun, Xiaowu, et al.
Published: (2025)
by: Sun, Xiaowu, et al.
Published: (2025)
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
by: Chen, Jungang, et al.
Published: (2023)
by: Chen, Jungang, et al.
Published: (2023)
Understanding Variable Performance on Deep MIL Framework for the Acoustic Detection of Tropical Birds
by: Jorge Castro
Published: (2020)
by: Jorge Castro
Published: (2020)
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
by: Höfler, Matthias, et al.
Published: (2025)
by: Höfler, Matthias, et al.
Published: (2025)
Control of dynamical systems with neural networks
by: Böttcher, Lucas
Published: (2025)
by: Böttcher, Lucas
Published: (2025)
OceanNet: A principled neural operator-based digital twin for regional oceans
by: Chattopadhyay, Ashesh, et al.
Published: (2023)
by: Chattopadhyay, Ashesh, et al.
Published: (2023)
Node Assigned physics-informed neural networks for thermal-hydraulic system simulation: CVH/FL module
by: Shin, Jeesuk, et al.
Published: (2025)
by: Shin, Jeesuk, et al.
Published: (2025)
Flow reconstruction in time-varying geometries using graph neural networks
by: Danciu, Bogdan A., et al.
Published: (2024)
by: Danciu, Bogdan A., et al.
Published: (2024)
Similar Items
-
Thermodynamics-informed graph neural networks for real-time simulation of digital human twins
by: Tesán, Lucas, et al.
Published: (2024) -
On the under-reaching phenomenon in message-passing neural PDE solvers: revisiting the CFL condition
by: Tesan, Lucas, et al.
Published: (2025) -
Graph neural networks informed locally by thermodynamics
by: Tierz, Alicia, et al.
Published: (2024) -
Preprint, models and results: Biologically informed neural network models are robust to spurious interactions via self-pruning
by: Nordenstorm, Olof
Published: (2025) -
The impact of neural network optimization on real-time cloud decision systems
by: Priya Narayanan
Published: (2025)