Saved in:
| Main Authors: | Qi, Miao, Idoughi, Ramzi, Heidrich, Wolfgang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.08570 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024)
by: Hu, Yaochen, et al.
Published: (2024)
Epi$^2$-Net: Advancing Epidemic Dynamics Forecasting with Physics-Inspired Neural Networks
by: Sun, Rui, et al.
Published: (2025)
by: Sun, Rui, et al.
Published: (2025)
Low-Rank Tensor Decompositions for the Theory of Neural Networks
by: Borsoi, Ricardo, et al.
Published: (2025)
by: Borsoi, Ricardo, et al.
Published: (2025)
Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting
by: Cao, Lingxiao, et al.
Published: (2025)
by: Cao, Lingxiao, et al.
Published: (2025)
Studying and Improving Graph Neural Network-based Motif Estimation
by: Vieira, Pedro C., et al.
Published: (2025)
by: Vieira, Pedro C., et al.
Published: (2025)
Flow to Learn: Flow Matching on Neural Network Parameters
by: Saragih, Daniel, et al.
Published: (2025)
by: Saragih, Daniel, et al.
Published: (2025)
$PINN - a Domain Decomposition Method for Bayesian Physics-Informed Neural Networks
by: Figueres, Júlia Vicens, et al.
Published: (2025)
by: Figueres, Júlia Vicens, et al.
Published: (2025)
Generalizability of Memorization Neural Networks
by: Yu, Lijia, et al.
Published: (2024)
by: Yu, Lijia, et al.
Published: (2024)
SP2RINT: Spatially-Decoupled Physics-Inspired Progressive Inverse Optimization for Scalable, PDE-Constrained Meta-Optical Neural Network Training
by: Ma, Pingchuan, et al.
Published: (2025)
by: Ma, Pingchuan, et al.
Published: (2025)
Clustering-based Multitasking Deep Neural Network for Solar Photovoltaics Power Generation Prediction
by: Song, Hui, et al.
Published: (2024)
by: Song, Hui, et al.
Published: (2024)
Unveiling Options with Neural Decomposition
by: Alikhasi, Mahdi, et al.
Published: (2024)
by: Alikhasi, Mahdi, et al.
Published: (2024)
Q-Net: Queue Length Estimation via Kalman-based Neural Networks
by: Gao, Ting, et al.
Published: (2025)
by: Gao, Ting, et al.
Published: (2025)
Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation
by: Pamshetti, Vijay Babu, et al.
Published: (2025)
by: Pamshetti, Vijay Babu, et al.
Published: (2025)
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024)
by: Chakraborty, Biswadeep, et al.
Published: (2024)
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)
by: You, Haoran, et al.
Published: (2022)
FlowX: Towards Explainable Graph Neural Networks via Message Flows
by: Gui, Shurui, et al.
Published: (2022)
by: Gui, Shurui, et al.
Published: (2022)
Bridging Computational Social Science and Deep Learning: Cultural Dissemination-Inspired Graph Neural Networks
by: Hevapathige, Asela
Published: (2025)
by: Hevapathige, Asela
Published: (2025)
Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks
by: Qi, Yijiashun, et al.
Published: (2026)
by: Qi, Yijiashun, et al.
Published: (2026)
Fractional Differential Equation Physics-Informed Neural Network and Its Application in Battery State Estimation
by: Dang, Lujuan, et al.
Published: (2025)
by: Dang, Lujuan, et al.
Published: (2025)
PIORF: Physics-Informed Ollivier-Ricci Flow for Long-Range Interactions in Mesh Graph Neural Networks
by: Yu, Youn-Yeol, et al.
Published: (2025)
by: Yu, Youn-Yeol, et al.
Published: (2025)
Physics-Informed Neural Networks for Satellite State Estimation
by: Varey, Jacob, et al.
Published: (2024)
by: Varey, Jacob, et al.
Published: (2024)
KIPPO: Koopman-Inspired Proximal Policy Optimization
by: Cozma, Andrei, et al.
Published: (2025)
by: Cozma, Andrei, et al.
Published: (2025)
Neural Network Optimal Power Flow via Energy Gradient Flow and Unified Dynamics
by: Liu, Xuezhi
Published: (2025)
by: Liu, Xuezhi
Published: (2025)
Physics-Inspired Spatial Temporal Graph Neural Networks for Predicting Industrial Chain Resilience
by: Wang, Bicheng, et al.
Published: (2025)
by: Wang, Bicheng, et al.
Published: (2025)
Gradient Flow Convergence Guarantee for General Neural Network Architectures
by: Jakhmola, Yash
Published: (2025)
by: Jakhmola, Yash
Published: (2025)
Neural Network-based Vehicular Channel Estimation Performance: Effect of Noise in the Training Set
by: Ngorima, Simbarashe Aldrin, et al.
Published: (2025)
by: Ngorima, Simbarashe Aldrin, et al.
Published: (2025)
Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks
by: Qi, Binchuan
Published: (2026)
by: Qi, Binchuan
Published: (2026)
Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023)
by: Xiong, Miao, et al.
Published: (2023)
ComFairGNN: Community Fair Graph Neural Network
by: Sium, Yonas, et al.
Published: (2024)
by: Sium, Yonas, et al.
Published: (2024)
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
by: Xu, Qi, et al.
Published: (2025)
by: Xu, Qi, et al.
Published: (2025)
Damper-B-PINN: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Vehicle State Estimation
by: Zeng, Tianyi, et al.
Published: (2025)
by: Zeng, Tianyi, et al.
Published: (2025)
Physics-Informed Neural Networks and Extensions
by: Raissi, Maziar, et al.
Published: (2024)
by: Raissi, Maziar, et al.
Published: (2024)
Complex Physics-Informed Neural Network
by: Si, Chenhao, et al.
Published: (2025)
by: Si, Chenhao, et al.
Published: (2025)
LLS: Local Learning Rule for Deep Neural Networks Inspired by Neural Activity Synchronization
by: Apolinario, Marco Paul E., et al.
Published: (2024)
by: Apolinario, Marco Paul E., et al.
Published: (2024)
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
by: Schnaus, Dominik, et al.
Published: (2023)
by: Schnaus, Dominik, et al.
Published: (2023)
Physics-Inspired Interpretability Of Machine Learning Models
by: Niroomand, Maximilian P, et al.
Published: (2023)
by: Niroomand, Maximilian P, et al.
Published: (2023)
Binarizing Physics-Inspired GNNs for Combinatorial Optimization
by: Krutský, Martin, et al.
Published: (2025)
by: Krutský, Martin, et al.
Published: (2025)
Deep Multi-View Channel-Wise Spatio-Temporal Network for Traffic Flow Prediction
by: Miao, Hao, et al.
Published: (2024)
by: Miao, Hao, et al.
Published: (2024)
Towards Generalization of Graph Neural Networks for AC Optimal Power Flow
by: Arowolo, Olayiwola, et al.
Published: (2025)
by: Arowolo, Olayiwola, et al.
Published: (2025)
Q-function Decomposition with Intervention Semantics with Factored Action Spaces
by: Lee, Junkyu, et al.
Published: (2025)
by: Lee, Junkyu, et al.
Published: (2025)
Similar Items
-
Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024) -
Epi$^2$-Net: Advancing Epidemic Dynamics Forecasting with Physics-Inspired Neural Networks
by: Sun, Rui, et al.
Published: (2025) -
Low-Rank Tensor Decompositions for the Theory of Neural Networks
by: Borsoi, Ricardo, et al.
Published: (2025) -
Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting
by: Cao, Lingxiao, et al.
Published: (2025) -
Studying and Improving Graph Neural Network-based Motif Estimation
by: Vieira, Pedro C., et al.
Published: (2025)