Saved in:
| Main Authors: | Jahani-nasab, Mahyar, Bijarchi, Mohamad Ali |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.10388 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Convergence Speed with Feature-Enforcing Physics-Informed Neural Networks: Utilizing Boundary Conditions as Prior Knowledge for Faster Convergence
by: Jahaninasab, Mahyar, et al.
Published: (2023)
by: Jahaninasab, Mahyar, et al.
Published: (2023)
Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
by: Hassanzadeh, Meraj, et al.
Published: (2025)
by: Hassanzadeh, Meraj, et al.
Published: (2025)
FlexPINN: Modeling Fluid Dynamics and Mass Transfer in 3D Micromixer Geometries Using a Flexible Physics-Informed Neural Network
by: Hassanzadeh, Meraj, et al.
Published: (2025)
by: Hassanzadeh, Meraj, et al.
Published: (2025)
Energy-Efficient Spiking Recurrent Neural Network for Gesture Recognition on Embedded GPUs
by: Varposhti, Marzieh Hassanshahi, et al.
Published: (2024)
by: Varposhti, Marzieh Hassanshahi, et al.
Published: (2024)
Provable Bounds on the Hessian of Neural Networks: Derivative-Preserving Reachability Analysis
by: Sharifi, Sina, et al.
Published: (2024)
by: Sharifi, Sina, et al.
Published: (2024)
Model Based and Physics Informed Deep Learning Neural Network Structures
by: Mohammad-Djafari, Ali, et al.
Published: (2024)
by: Mohammad-Djafari, Ali, et al.
Published: (2024)
Equation Discovery, Parametric Simulation, and Optimization Using the Physics-Informed Neural Network (PINN) Method for the Heat Conduction Problem
by: Ghaderi, Ehsan, et al.
Published: (2025)
by: Ghaderi, Ehsan, et al.
Published: (2025)
Per-Loss Adapters for Gradient Conflict in Physics-Informed Neural Networks
by: Kim, Bum Jun, et al.
Published: (2026)
by: Kim, Bum Jun, et al.
Published: (2026)
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
by: Dashtbayaz, Nima Hosseini, et al.
Published: (2024)
by: Dashtbayaz, Nima Hosseini, et al.
Published: (2024)
Loss Terms and Operator Forms of Koopman Autoencoders
by: Enyeart, Dustin, et al.
Published: (2024)
by: Enyeart, Dustin, et al.
Published: (2024)
Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
by: Miranda, Miro, et al.
Published: (2024)
by: Miranda, Miro, et al.
Published: (2024)
Physics-Informed Neural Networks with Learnable Loss Balancing and Transfer Learning
by: Pirayeshshirazinezhad, Reza
Published: (2026)
by: Pirayeshshirazinezhad, Reza
Published: (2026)
Learning from Integral Losses in Physics Informed Neural Networks
by: Saleh, Ehsan, et al.
Published: (2023)
by: Saleh, Ehsan, et al.
Published: (2023)
Physics-Informed Neural Networks with Unknown Partial Differential Equations: an Application in Multivariate Time Series
by: Mortezanejad, Seyedeh Azadeh Fallah, et al.
Published: (2025)
by: Mortezanejad, Seyedeh Azadeh Fallah, et al.
Published: (2025)
Physics-Informed Neural Networks for Solving Derivative-Constrained PDEs
by: Hoshisashi, Kentaro, et al.
Published: (2026)
by: Hoshisashi, Kentaro, et al.
Published: (2026)
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
by: Chu, Haoyu, et al.
Published: (2024)
by: Chu, Haoyu, et al.
Published: (2024)
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators
by: Gan, Weiye, et al.
Published: (2025)
by: Gan, Weiye, et al.
Published: (2025)
Bayesian Physics Informed Neural Networks for Linear Inverse problems
by: Mohammad-Djafari, Ali
Published: (2025)
by: Mohammad-Djafari, Ali
Published: (2025)
Continuous-Time Piecewise-Linear Recurrent Neural Networks
by: Brändle, Alena, et al.
Published: (2026)
by: Brändle, Alena, et al.
Published: (2026)
Time-Warping Recurrent Neural Networks for Transfer Learning
by: Hirschi, Jonathon
Published: (2026)
by: Hirschi, Jonathon
Published: (2026)
Physics-Informed Neural Networks for Shell Structures
by: Bastek, Jan-Hendrik, et al.
Published: (2022)
by: Bastek, Jan-Hendrik, et al.
Published: (2022)
Recurrent Neural Networks with Linear Structures for Electricity Price Forecasting
by: Amor, Souhir Ben, et al.
Published: (2025)
by: Amor, Souhir Ben, et al.
Published: (2025)
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
by: Chou, Yi En, et al.
Published: (2025)
by: Chou, Yi En, et al.
Published: (2025)
Conformalized Physics-Informed Neural Networks
by: Podina, Lena, et al.
Published: (2024)
by: Podina, Lena, et al.
Published: (2024)
Integrating Biological-Informed Recurrent Neural Networks for Glucose-Insulin Dynamics Modeling
by: De Carli, Stefano, et al.
Published: (2025)
by: De Carli, Stefano, et al.
Published: (2025)
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks
by: Michałowska, Katarzyna, et al.
Published: (2023)
by: Michałowska, Katarzyna, et al.
Published: (2023)
Deep State Space Recurrent Neural Networks for Time Series Forecasting
by: Inzirillo, Hugo
Published: (2024)
by: Inzirillo, Hugo
Published: (2024)
SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks
by: Anticev, John, et al.
Published: (2024)
by: Anticev, John, et al.
Published: (2024)
Numerical simulation of transient heat conduction with moving heat source using Physics Informed Neural Networks
by: Kalyan, Anirudh, et al.
Published: (2025)
by: Kalyan, Anirudh, et al.
Published: (2025)
Recurrent U-Net-Based Graph Neural Network (RUGNN) for Accurate Deformation Predictions in Sheet Material Forming
by: Zhao, Yingxue, et al.
Published: (2025)
by: Zhao, Yingxue, et al.
Published: (2025)
Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
by: Le, Hung, et al.
Published: (2025)
by: Le, Hung, et al.
Published: (2025)
RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks
by: Hou, Haowen, et al.
Published: (2024)
by: Hou, Haowen, et al.
Published: (2024)
Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification
by: Entesari, Taha, et al.
Published: (2026)
by: Entesari, Taha, et al.
Published: (2026)
Fourier-Enhanced Recurrent Neural Networks for Electrical Load Time Series Downscaling
by: Chen, Qi, et al.
Published: (2025)
by: Chen, Qi, et al.
Published: (2025)
ParaRNN: An Interpretable and Parallelizable Recurrent Neural Network for Time-Dependent Data
by: Cai, Yuxi, et al.
Published: (2026)
by: Cai, Yuxi, et al.
Published: (2026)
Actor-Critic Physics-informed Neural Lyapunov Control
by: Wang, Jiarui, et al.
Published: (2024)
by: Wang, Jiarui, et al.
Published: (2024)
Investigating Sparsity in Recurrent Neural Networks
by: Darji, Harshil
Published: (2024)
by: Darji, Harshil
Published: (2024)
Preconditioning for Physics-Informed Neural Networks
by: Liu, Songming, et al.
Published: (2024)
by: Liu, Songming, et al.
Published: (2024)
Physics-Informed Neural Networks and Extensions
by: Raissi, Maziar, et al.
Published: (2024)
by: Raissi, Maziar, et al.
Published: (2024)
Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)
by: Furuya, Takashi, et al.
Published: (2021)
Similar Items
-
Enhancing Convergence Speed with Feature-Enforcing Physics-Informed Neural Networks: Utilizing Boundary Conditions as Prior Knowledge for Faster Convergence
by: Jahaninasab, Mahyar, et al.
Published: (2023) -
Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
by: Hassanzadeh, Meraj, et al.
Published: (2025) -
FlexPINN: Modeling Fluid Dynamics and Mass Transfer in 3D Micromixer Geometries Using a Flexible Physics-Informed Neural Network
by: Hassanzadeh, Meraj, et al.
Published: (2025) -
Energy-Efficient Spiking Recurrent Neural Network for Gesture Recognition on Embedded GPUs
by: Varposhti, Marzieh Hassanshahi, et al.
Published: (2024) -
Provable Bounds on the Hessian of Neural Networks: Derivative-Preserving Reachability Analysis
by: Sharifi, Sina, et al.
Published: (2024)