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20232026
most citedAdaptive-Growth Randomized Neural Networks for PDEs: Algorithms and Numerical Analysis

4 citations · 4 across the 8 of their papers we have counts for

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math.NA2026

Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains

Haixin Wang, Haoning Dang, Fei Wang +1

Partial differential equations on unbounded domains are challenging because the exterior region must be represented without excessive truncation error. Truncation-based methods oft…

math.NA2026

Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

Haoning Dang, Fei Wang, Yifan Chen +3

Integro-differential equations arise in a wide range of applications, including transport, kinetic theory, radiative transfer, and multiphysics modeling, where nonlocal integral op…

math.NA2026

Adaptive-Growth Randomized Neural Networks for Level-Set Computation of Multivalued Nonlinear First-Order PDEs with Hyperbolic Characteristics

Haoning Dang, Shi Jin, Fei Wang

This paper proposes an Adaptive-Growth Randomized Neural Network (AG-RaNN) method for computing multivalued solutions of nonlinear first-order PDEs with hyperbolic characteristics,…