A Model-Guided Neural Network Method for the Inverse Scattering Problem
Fuente:
arXiv
Saved in:
| Main Authors: | Tsang, Olivia, Melia, Owen, Charisopoulos, Vasileios, Hoskins, Jeremy, Khoo, Yuehaw, Willett, Rebecca |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Frequency Progressive Refinement for Learned Inverse Scattering
by: Melia, Owen, et al.
Published: (2024)
by: Melia, Owen, et al.
Published: (2024)
Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay
by: Laus, Hannah, et al.
Published: (2025)
by: Laus, Hannah, et al.
Published: (2025)
How do simple rotations affect the implicit bias of Adam?
by: DePavia, Adela, et al.
Published: (2025)
by: DePavia, Adela, et al.
Published: (2025)
Reinforced Inverse Scattering
by: Jiang, Hanyang, et al.
Published: (2022)
by: Jiang, Hanyang, et al.
Published: (2022)
Deep Neural-network Prior for Orbit Recovery from Method of Moments
by: Khoo, Yuehaw, et al.
Published: (2023)
by: Khoo, Yuehaw, et al.
Published: (2023)
Nonlinear tomographic reconstruction via nonsmooth optimization
by: Charisopoulos, Vasileios, et al.
Published: (2024)
by: Charisopoulos, Vasileios, et al.
Published: (2024)
Contrast-Source-Based Physics-Driven Neural Network for Inverse Scattering Problems
by: Du, Yutong, et al.
Published: (2026)
by: Du, Yutong, et al.
Published: (2026)
jaxhps: An elliptic PDE solver built with machine learning in mind
by: Melia, Owen, et al.
Published: (2025)
by: Melia, Owen, et al.
Published: (2025)
Hardware Acceleration for HPS Algorithms in Two and Three Dimensions
by: Melia, Owen, et al.
Published: (2025)
by: Melia, Owen, et al.
Published: (2025)
Physics-Driven Neural Network for Solving Electromagnetic Inverse Scattering Problems
by: Du, Yutong, et al.
Published: (2025)
by: Du, Yutong, et al.
Published: (2025)
Sketch Tomography: Hybridizing Classical Shadow and Matrix Product State
by: Tang, Xun, et al.
Published: (2025)
by: Tang, Xun, et al.
Published: (2025)
Fast Physics-Driven Untrained Network for Highly Nonlinear Inverse Scattering Problems
by: Du, Yutong, et al.
Published: (2026)
by: Du, Yutong, et al.
Published: (2026)
Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization
by: DePavia, Adela, et al.
Published: (2025)
by: DePavia, Adela, et al.
Published: (2025)
TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems
by: Nguyen, Hai V., et al.
Published: (2024)
by: Nguyen, Hai V., et al.
Published: (2024)
Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems
by: Jekic, Aleksandra, et al.
Published: (2025)
by: Jekic, Aleksandra, et al.
Published: (2025)
Local linear convergence of gradient methods for overparameterized Gaussian mixtures
by: Wang, Jingxing, et al.
Published: (2026)
by: Wang, Jingxing, et al.
Published: (2026)
Robust Point Matching with Distance Profiles
by: Hur, YoonHaeng, et al.
Published: (2023)
by: Hur, YoonHaeng, et al.
Published: (2023)
Physics-Informed Deep Contrast Source Inversion: A Unified Framework for Inverse Scattering Problems
by: Sun, Haoran, et al.
Published: (2025)
by: Sun, Haoran, et al.
Published: (2025)
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
by: Parkinson, Suzanna, et al.
Published: (2023)
by: Parkinson, Suzanna, et al.
Published: (2023)
PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems
by: Goel, Divyam, et al.
Published: (2026)
by: Goel, Divyam, et al.
Published: (2026)
Diffusion-Based Electromagnetic Inverse Design of Scattering Structured Media
by: Tsukerman, Mikhail, et al.
Published: (2025)
by: Tsukerman, Mikhail, et al.
Published: (2025)
Multivariate Density Estimation via Variance-Reduced Sketching
by: Peng, Yifan, et al.
Published: (2024)
by: Peng, Yifan, et al.
Published: (2024)
Efficient Deconvolution in Populational Inverse Problems
by: Vadeboncoeur, Arnaud, et al.
Published: (2025)
by: Vadeboncoeur, Arnaud, et al.
Published: (2025)
Forward and Inverse Simulation of Pseudo-Two-Dimensional Model of Lithium-Ion Batteries Using Neural Networks
by: Lee, Myeong-Su, et al.
Published: (2024)
by: Lee, Myeong-Su, et al.
Published: (2024)
Multi-frequency Neural Born Iterative Method for Solving 2-D Inverse Scattering Problems
by: Liu, Daoqi, et al.
Published: (2024)
by: Liu, Daoqi, et al.
Published: (2024)
Improved Physics-Driven Neural Network to Solve Inverse Scattering Problems
by: Du, Yutong, et al.
Published: (2025)
by: Du, Yutong, et al.
Published: (2025)
Inverse Modeling of Dielectric Response in Time Domain using Physics-Informed Neural Networks
by: Esenov, Emir, et al.
Published: (2025)
by: Esenov, Emir, et al.
Published: (2025)
Optimization-Free Diffusion Model -- A Perturbation Theory Approach
by: Khoo, Yuehaw, et al.
Published: (2025)
by: Khoo, Yuehaw, et al.
Published: (2025)
Uncertainties in Physics-informed Inverse Problems: The Hidden Risk in Scientific AI
by: Mototake, Yoh-ichi, et al.
Published: (2025)
by: Mototake, Yoh-ichi, et al.
Published: (2025)
Combining Monte Carlo and Tensor-network Methods for Partial Differential Equations via Sketching
by: Chen, Yian, et al.
Published: (2023)
by: Chen, Yian, et al.
Published: (2023)
Advancing Physics Data Analysis through Machine Learning and Physics-Informed Neural Networks
by: Vatellis, Vasileios
Published: (2024)
by: Vatellis, Vasileios
Published: (2024)
Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
by: Zhang, Borong, et al.
Published: (2022)
by: Zhang, Borong, et al.
Published: (2022)
A Two-Stage Imaging Framework Combining CNN and Physics-Informed Neural Networks for Full-Inverse Tomography: A Case Study in Electrical Impedance Tomography (EIT)
by: Yang, Xuanxuan, et al.
Published: (2024)
by: Yang, Xuanxuan, et al.
Published: (2024)
Understanding Neural Network Systems for Image Analysis using Vector Spaces and Inverse Maps
by: Pattichis, Rebecca, et al.
Published: (2024)
by: Pattichis, Rebecca, et al.
Published: (2024)
Depth Separation in Norm-Bounded Infinite-Width Neural Networks
by: Parkinson, Suzanna, et al.
Published: (2024)
by: Parkinson, Suzanna, et al.
Published: (2024)
Generative Modeling via Hierarchical Tensor Sketching
by: Peng, Yifan, et al.
Published: (2023)
by: Peng, Yifan, et al.
Published: (2023)
Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet
by: Adrian, Melissa, et al.
Published: (2024)
by: Adrian, Melissa, et al.
Published: (2024)
Bayesian Inference for PDE-based Inverse Problems using the Optimization of a Discrete Loss
by: Amoudruz, Lucas, et al.
Published: (2025)
by: Amoudruz, Lucas, et al.
Published: (2025)
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
by: Orlova, Elena, et al.
Published: (2022)
by: Orlova, Elena, et al.
Published: (2022)
DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models
by: Wang, Hengkang, et al.
Published: (2024)
by: Wang, Hengkang, et al.
Published: (2024)
Similar Items
-
Multi-Frequency Progressive Refinement for Learned Inverse Scattering
by: Melia, Owen, et al.
Published: (2024) -
Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay
by: Laus, Hannah, et al.
Published: (2025) -
How do simple rotations affect the implicit bias of Adam?
by: DePavia, Adela, et al.
Published: (2025) -
Reinforced Inverse Scattering
by: Jiang, Hanyang, et al.
Published: (2022) -
Deep Neural-network Prior for Orbit Recovery from Method of Moments
by: Khoo, Yuehaw, et al.
Published: (2023)