Probabilistic Inference on Noisy Time Series
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Updated
Jun 13, 2024 - Python
Probabilistic Inference on Noisy Time Series
A collection of inverse design challenges
PyTorch library for solving imaging inverse problems using deep learning
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
Forward modeling, inversion, and processing gravity and magnetic data
The Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN
Scientific Computational Imaging COde
Inverse modelling framework for dynamical systems characterised by complex dynamics.
Learning Partial Differential Equations by Spectral Approximates of General Sobolev Spaces
Differentiable solver for time-dependent deformation problems with contact
Learning Diffusion Priors from Observations by Expectation Maximization
The aim of this repository is to create a Flow-Matching-based model capable of doing text2img, solving inverse problems: jpeg restoration, debluring, denoising, superres, coloring, inpainting, outpainting.
Algorithms for inverse design
Custom types for topology optimization
PyProximal – Proximal Operators and Algorithms in Python
Lensless imaging toolkit. Complete tutorial: https://go.epfl.ch/lenslesspicam
Diffusion modeling code and notebooks
The set of CPU/GPU optimised regularisation modules for iterative image reconstruction and other image processing tasks
PyLops – A Linear-Operator Library for Python
ChaosMagPy is a simple Python package for evaluating the CHAOS geomagnetic field model and other models of Earth's magnetic field.
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