Saved in:
| Main Authors: | Salim, Joshua, Yu, Jordan, Zhao, Xilei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.21666 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Synthesizing Attitudes, Predicting Actions (SAPA): Behavioral Theory-Guided LLMs for Ridesourcing Mode Choice Modeling
by: Sameen, Mustafa, et al.
Published: (2025)
by: Sameen, Mustafa, et al.
Published: (2025)
Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023)
by: Xiong, Miao, et al.
Published: (2023)
SEANN: A Domain-Informed Neural Network for Epidemiological Insights
by: Guimbaud, Jean-Baptiste, et al.
Published: (2025)
by: Guimbaud, Jean-Baptiste, et al.
Published: (2025)
Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning
by: Sun, Yuran, et al.
Published: (2025)
by: Sun, Yuran, et al.
Published: (2025)
SMiLE: Provably Enforcing Global Relational Properties in Neural Networks
by: Francobaldi, Matteo, et al.
Published: (2025)
by: Francobaldi, Matteo, et al.
Published: (2025)
Rethinking Input Domains in Physics-Informed Neural Networks via Geometric Compactification Mappings
by: Huang, Zhenzhen, et al.
Published: (2026)
by: Huang, Zhenzhen, et al.
Published: (2026)
Do Deep Neural Network Solutions Form a Star Domain?
by: Sonthalia, Ankit, et al.
Published: (2024)
by: Sonthalia, Ankit, et al.
Published: (2024)
Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
by: Ganguly, Abhisek, et al.
Published: (2026)
by: Ganguly, Abhisek, et al.
Published: (2026)
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
by: Sartor, Davide, et al.
Published: (2025)
by: Sartor, Davide, et al.
Published: (2025)
Smooth Min-Max Monotonic Networks
by: Igel, Christian
Published: (2023)
by: Igel, Christian
Published: (2023)
Deep Model Merging: The Sister of Neural Network Interpretability -- A Survey
by: Khan, Arham, et al.
Published: (2024)
by: Khan, Arham, et al.
Published: (2024)
DKINet: Medication Recommendation via Domain Knowledge Informed Deep Learning
by: Liu, Sicen, et al.
Published: (2023)
by: Liu, Sicen, et al.
Published: (2023)
Monotone and Separable Set Functions: Characterizations and Neural Models
by: Sarangi, Soutrik, et al.
Published: (2025)
by: Sarangi, Soutrik, et al.
Published: (2025)
Enforcing Orderedness to Improve Feature Consistency
by: Wang, Sophie L., et al.
Published: (2025)
by: Wang, Sophie L., 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)
Certifying Global Robustness for Deep Neural Networks
by: Li, You, et al.
Published: (2024)
by: Li, You, et al.
Published: (2024)
Complex Physics-Informed Neural Network
by: Si, Chenhao, et al.
Published: (2025)
by: Si, Chenhao, et al.
Published: (2025)
Physics-Informed Neural Networks and Extensions
by: Raissi, Maziar, et al.
Published: (2024)
by: Raissi, Maziar, et al.
Published: (2024)
LION-DG: Layer-Informed Initialization with Deep Gradient Protocols for Accelerated Neural Network Training
by: Kim, Hyunjun
Published: (2026)
by: Kim, Hyunjun
Published: (2026)
GINN-KAN: Interpretability pipelining with applications in Physics Informed Neural Networks
by: Ranasinghe, Nisal, et al.
Published: (2024)
by: Ranasinghe, Nisal, et al.
Published: (2024)
ARNN: Attentive Recurrent Neural Network for Multi-channel EEG Signals to Identify Epileptic Seizures
by: Rukhsar, Salim, et al.
Published: (2024)
by: Rukhsar, Salim, et al.
Published: (2024)
Supervised Dynamic Dimension Reduction with Deep Neural Network
by: Luo, Zhanye, et al.
Published: (2025)
by: Luo, Zhanye, et al.
Published: (2025)
GradINN: Gradient Informed Neural Network
by: Aglietti, Filippo, et al.
Published: (2024)
by: Aglietti, Filippo, et al.
Published: (2024)
Densely Multiplied Physics Informed Neural Networks
by: Jiang, Feilong, et al.
Published: (2024)
by: Jiang, Feilong, et al.
Published: (2024)
AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity
by: Yu, Yeyong, et al.
Published: (2025)
by: Yu, Yeyong, et al.
Published: (2025)
Anomaly Detection Based on Critical Paths for Deep Neural Networks
by: Zhao, Fangzhen, et al.
Published: (2025)
by: Zhao, Fangzhen, et al.
Published: (2025)
Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks
by: Mazandarani, Mehran, et al.
Published: (2025)
by: Mazandarani, Mehran, et al.
Published: (2025)
Symmetry in Neural Network Parameter Spaces
by: Zhao, Bo, et al.
Published: (2025)
by: Zhao, Bo, et al.
Published: (2025)
Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
by: Jin, Ming, et al.
Published: (2023)
by: Jin, Ming, et al.
Published: (2023)
Wormhole Dynamics in Deep Neural Networks
by: Lai, Yen-Lung, et al.
Published: (2025)
by: Lai, Yen-Lung, et al.
Published: (2025)
Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)
by: Weng, Shudi, et al.
Published: (2026)
Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural Networks
by: Furlong, Aidan, et al.
Published: (2025)
by: Furlong, Aidan, et al.
Published: (2025)
Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations
by: Wei, Zhao, et al.
Published: (2026)
by: Wei, Zhao, et al.
Published: (2026)
Physics-Informed Graph Neural Networks for Water Distribution Systems
by: Ashraf, Inaam, et al.
Published: (2024)
by: Ashraf, Inaam, et al.
Published: (2024)
Improved Training of Physics-Informed Neural Networks with Model Ensembles
by: Haitsiukevich, Katsiaryna, et al.
Published: (2022)
by: Haitsiukevich, Katsiaryna, et al.
Published: (2022)
Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks
by: An, Kang, et al.
Published: (2026)
by: An, Kang, et al.
Published: (2026)
Meta-Learning and Knowledge Discovery based Physics-Informed Neural Network for Remaining Useful Life Prediction
by: Wang, Yu, et al.
Published: (2025)
by: Wang, Yu, et al.
Published: (2025)
Evidential Physics-Informed Neural Networks
by: Tan, Hai Siong, et al.
Published: (2025)
by: Tan, Hai Siong, et al.
Published: (2025)
AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs
by: Dang, Ting, et al.
Published: (2026)
by: Dang, Ting, et al.
Published: (2026)
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
by: Huang, Zijie, et al.
Published: (2024)
by: Huang, Zijie, et al.
Published: (2024)
Similar Items
-
Synthesizing Attitudes, Predicting Actions (SAPA): Behavioral Theory-Guided LLMs for Ridesourcing Mode Choice Modeling
by: Sameen, Mustafa, et al.
Published: (2025) -
Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023) -
SEANN: A Domain-Informed Neural Network for Epidemiological Insights
by: Guimbaud, Jean-Baptiste, et al.
Published: (2025) -
Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning
by: Sun, Yuran, et al.
Published: (2025) -
SMiLE: Provably Enforcing Global Relational Properties in Neural Networks
by: Francobaldi, Matteo, et al.
Published: (2025)