causality-aware training 1partial differential equations 1physics-informed neural networks 1shock waves 1spectral methods 1stiff problems 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
SPARC-Net: A Spectral, Causality-Aware, and Hard-Constrained Physics-Informed Architecture for Stiff and Shock-Dominated Partial Differential Equations
Divyavardhan Singh, Dimple Sonone, Hammad Mohammad +1
The paper introduces SPARC-Net, a physics-informed neural network architecture that combines spectral encoding, causality-aware training, and hard constraints to improve the soluti…
cs.CV2026
NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Suhang Yao +95
This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…
cs.LG2026
Stabilized Adaptive Loss and Residual-Based Collocation for Physics-Informed Neural Networks
Divyavardhan Singh, Shubham Kamble, Dimple Sonone +1
Physics-Informed Neural Networks (PINNs) have been recognized as a mesh-free alternative to solve partial differential equations where physics information is incorporated. However,…