polarization

Comprehensive optical design, optimization, and analysis in Python, including GPU-accelerated and differentiable ray tracing via PyTorch.

Polarization image analysis tool. Demosaicing, Stokes vector, Mueller matrix.

Proton Exchange Membrane (PEM) Fuel Cell Dataset

Monte Carlo and Molecular Dynamics Simulation Package

Official Pytorch implementation of PANDORA: Polarization-Aided Neural Decomposition of Radiance

XLuminA, a highly-efficient, auto-differentiating discovery framework for super-resolution microscopy.

3D Monte Carlo radiative transfer code

pySCATMECH is a Python interface to SCATMECH: Polarized Light Scattering C++ Class Library

Training for multi-modal image fusion with PyTorch.

SCATMECH: Polarized light scattering C++ class library

Wave optical models and inverse algorithms for label-agnostic imaging of density & orientation.

3D virtual staining with 2D and 2.5D U-Nets

CVPR 2024: Robust Depth Enhancement via Polarization Prompt Fusion Tuning

Single DBFC Dataset

This collection of codes can be used for extracting features from continuous seismic signals for different machine learning tasks.

PySM: Software for simulating the Galactic microwave sky

Pynkowski is a Python package to compute Minkowski Functionals, as well as their expected values for different fields.

Hazel v2.0: synthesis and inversion of Stokes profiles caused by the joint action of atomic level polarization and the Hanle and Zeeman effects

SP-TFF code package aims to present a methodology for high-resolution polarization analysis and filtering of seismic signals in the TF-domain. The main developments in this research work are: (a) reformulation of the eigenvalue decomposition polarization analysis (EDPA) in TF-domain, (b) combining the SP-TFR to the formulation to obtain high-resolution TF-domains polarization parameters for discriminating nearby seismic phases, and (c) incorporating TF-domain directivity, rectilinearity, and amplitude attributes to extract (or eliminate) different seismic phases. The main focus is to discriminate between Love and Rayleigh from the body and coda waves.

Functions for analysis of high resolution electron microscopy and spectroscopy data.