An Open-Source Python Library for the development of algorithms for 2D Electromagnetic Inverse Scattering Problems.
-
Updated
Dec 19, 2025 - Python
An Open-Source Python Library for the development of algorithms for 2D Electromagnetic Inverse Scattering Problems.
Code for the main models described in “Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models”.
Python port of Redbird - a comprehensive DOT image reconstruction toolbox
This repository contains four baseline deterministic models and the U-ViT diffusion model for solving the wideband inverse scattering problem.
This instruction aims to reproduce the results in the paper “Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems” proposed by Sung, Wang, Cakoni, Harris, and Hung.
Scripts for the paper "Exploring the inverse line-source scattering problem in dielectric cylinders with deep neural networks". Authors: Nikolaos Pallikarakis, Andreas Kalogeropoulos and Nikolaos Tsitsas. Correspondence at npall@central.ntua.gr.
A solution, written in C, to Korteweg de Vries using the fourth order Runge-Kutta method and finite differences.
Rescuing Moore’s Law via Room-Temperature Soliton Integration in Standard Silicon.
Implements MATLAB simulations from the paper "Qualitative indicator functions for imaging crack networks using acoustic waves". Includes two inversion algorithms for crack detection based on far-field acoustic data.
Add a description, image, and links to the inverse-scattering topic page so that developers can more easily learn about it.
To associate your repository with the inverse-scattering topic, visit your repo's landing page and select "manage topics."