:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ka, Eunhan, Leclercq, Ludovic, Ukkusuri, Satish V.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Systems and Control 35L65, 65M99, 68T07, 90B20 I.2.6; G.1.8; J.2
Online Access:	https://arxiv.org/abs/2605.08028
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Classical-Quantum Hybrid Architecture for Physics-Informed Neural Networks
by: Lantigua, Said, et al.
Published: (2025)

PTL-PINNs: Perturbation-Guided Transfer Learning with Physics- Informed Neural Networks for Nonlinear Systems
by: Alexandrino, Duarte, et al.
Published: (2026)

Autoencoders in Function Space
by: Bunker, Justin, et al.
Published: (2024)

Stable Long-Horizon Neural ODE Reduced-Order Models via Learned Feedback for Biological Growth and Remodeling
by: Laudo, Joel, et al.
Published: (2026)

CAO: Curvature-Adaptive Optimization via Periodic Low-Rank Hessian Sketching
by: Du, Wenzhang
Published: (2025)

Stochastic Estimation of the Layer-wise Hessian Trace for Monitoring Neural-network Training
by: Bolshim, Maxim, et al.
Published: (2026)

Day-to-Day Traffic Network Modeling under Route-Guidance Misinformation: Endogenous Trust and Resilience in CAV Environments
by: Ka, Eunhan, et al.
Published: (2026)

Multi-Hypothesis Prediction for Portfolio Optimization: A Structured Ensemble Learning Approach to Risk Diversification
by: Dominguez, Alejandro Rodriguez, et al.
Published: (2025)

Refining Graphical Neural Network Predictions Using Flow Matching for Optimal Power Flow with Constraint-Satisfaction Guarantee
by: Khanal, Kshitiz
Published: (2025)

Solving High Dimensional Partial Differential Equations Using Tensor Neural Network and A Posteriori Error Estimators
by: Wang, Yifan, et al.
Published: (2023)

Inter-Layer Hessian Analysis of Neural Networks with DAG Architectures
by: Bolshim, Maxim, et al.
Published: (2026)

Regime-Aware Time Weighting for Physics-Informed Neural Networks
by: Turinici, Gabriel
Published: (2024)

Separable Physics-Informed Neural Networks for the solution of elasticity problems
by: Es'kin, Vasiliy A., et al.
Published: (2024)

Adam Improves Muon: Adaptive Moment Estimation with Orthogonalized Momentum
by: Zhang, Minxin, et al.
Published: (2026)

Neural Ordinary Differential Equations for Model Order Reduction of Stiff Systems
by: Caldana, Matteo, et al.
Published: (2024)

Predictive Digital Twins for Thermal Management Using Machine Learning and Reduced-Order Models
by: Subramani, Tamilselvan, et al.
Published: (2025)

On the study of frequency control and spectral bias in Wavelet-Based Kolmogorov Arnold networks: A path to physics-informed KANs
by: Meshir, Juan Daniel, et al.
Published: (2025)

Modeling Vehicle-Type-Specific Pedestrian Crash Avoidance Behavior in Safety-Critical Interactions Using Smooth-Mamba Deep Reinforcement Learning
by: Pu, Qingwen, et al.
Published: (2026)

Fourier neural operator for learning solutions to macroscopic traffic flow models: Application to the forward and inverse problems
by: Thodi, Bilal Thonnam, et al.
Published: (2023)

Neural Network Element Method for Partial Differential Equations
by: Wang, Yifan, et al.
Published: (2025)

Regularity Analysis and Tensor Neural Network Methods for Quasiperiodic Elliptic Equations
by: Ren, Jingze, et al.
Published: (2026)

$δ$-STEAL: LLM Stealing Attack with Local Differential Privacy
by: Dang, Kieu, et al.
Published: (2025)

Layer-Parallel Training for Transformers
by: Jiang, Shuai, et al.
Published: (2026)

Stabilized Adaptive Loss and Residual-Based Collocation for Physics-Informed Neural Networks
by: Singh, Divyavardhan, et al.
Published: (2026)

Learning the P2D Model for Lithium-Ion Batteries with SOH Detection
by: McKay, Maricela Best, et al.
Published: (2025)

Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media
by: Fernández-Godino, M. Giselle, et al.
Published: (2025)

Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations
by: Kashi, Aditya, et al.
Published: (2024)

Local properties of neural networks through the lens of layer-wise Hessians
by: Bolshim, Maxim, et al.
Published: (2025)

Physics-Informed Learning of Microvascular Flow Models using Graph Neural Networks
by: Botta, Paolo, et al.
Published: (2025)

Are Two Hidden Layers Still Enough for the Physics-Informed Neural Networks?
by: Es'kin, Vasiliy A., et al.
Published: (2024)

Intrinsic-Metric Physics-Informed Neural Networks (IM-PINN) for Reaction-Diffusion Dynamics on Complex Riemannian Manifolds
by: Chrisnanto, Julian Evan, et al.
Published: (2025)

About rectified sigmoid function for enhancing the accuracy of Physics-Informed Neural Networks
by: Es'kin, Vasiliy A., et al.
Published: (2024)

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation
by: Xie, Runlong, et al.
Published: (2026)

Dual-Solver: A Generalized ODE Solver for Diffusion Models with Dual Prediction
by: Park, Soochul, et al.
Published: (2026)

Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations
by: Bitzer, Matthias, et al.
Published: (2024)

A Structure-Preserving Framework for Solving Parabolic Partial Differential Equations with Neural Networks
by: Chen, Gaohang, et al.
Published: (2025)

Solving Schrödinger Equation Using Tensor Neural Network
by: Liao, Yangfei, et al.
Published: (2022)

Physics-Informed Neural Networks: A Didactic Derivation of the Complete Training Cycle
by: Tahimi, Abdeladhim
Published: (2026)

FSampler: Training Free Acceleration of Diffusion Sampling via Epsilon Extrapolation
by: Vladimir, Michael A.
Published: (2025)

i-DEQ: A stable inertial deep equilibrium model for image restoration
by: Clerc, Antonin, et al.
Published: (2026)