Scientific Computational Imaging COde
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Updated
Sep 19, 2024 - Python
Scientific Computational Imaging COde
SAGECal is a fast, memory efficient and GPU accelerated radio interferometric calibration program. It supports all source models including points, Gaussians and Shapelets. Distributed calibration using MPI and consensus optimization is enabled. Both spectral and spatial priors can be used as constraints. Tools to build/restore sky models are inc…
Lensless imaging toolkit. Complete tutorial: https://go.epfl.ch/lenslesspicam
TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software
Python interactive interface for TinyMPC
R Package: Regularized Principal Component Analysis for Spatial Data
R Package: Regularized Spatial Maximum Covariance Analysis
R Package: Adaptively weighted group lasso for semiparametic quantile regression models
R Package: Regularized Principal Component Analysis for Spatial Data
R Package: Regularized Spatial Maximum Covariance Analysis
social Discrete Choice Models in Python
Proximal algorithms for nonsmooth optimization in Julia
Julia implementation of ADMM solver on multiple GPUs
R interface for OSQP
MATLAB interactive interface for TinyMPC
Sparse Optimisation Research Code
Distributed Multidisciplinary Design Optimization
Julia interactive interface for TinyMPC
Simulation code of our paper in IEEE Transactions on Cognitive Communications and Networking: ''Energy-Efficient Blockchain-enabled User-Centric Mobile Edge Computing''
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