inverse-scattering

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 Physics-Informed Neural Network (PINN) framework for quantitative ultrasound imaging. It reconstructs spatially varying sound speed maps directly from multi-view RF data to correct phase aberration.

A solution, written in C, to Korteweg de Vries using the fourth order Runge-Kutta method and finite differences.

2D TM electromagnetic inverse scattering with Born approximation and TSVD regularization

BEM Benchmark of the Ehrenpreis-Palamodov Gaussian Process for Maxwell Cavity Scattering

Rescuing Moore’s Law via Room-Temperature Soliton Integration in Standard Silicon.

Build a Gardner Logic-Bridge IP core for threshold-programmable, room-temperature soliton logic 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.

Hardened Scatt3D: 3D EM scattering FEM + S-parameter defect imaging — measured-data bug fixed, 3.3x faster solver, converging sweep mode, measurement diagnostics, tests, CI