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This collection contains the code used to analyze the data that supports the findings from the following publication:

Li et al, 2022 (https://doi.org/10.1088/1741-2552/ac9aaf)

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

PyTorch implementation of the SonoNet Ultrasound standard plane detector

Project for the Graph representation learning summer school (02901 Advanced Topics in Machine Learning course) at the Technical University of Denmark in August 2022.

The python code used for the numerical examples in the paper "Reconstructing anisotropic conductivities on two-dimensional Riemannian manifolds from power densities". A preprint of this paper is available on arXiv: https://arxiv.org/abs/2202.12056.

The python code used for the numerical examples in the paper "Conductivity reconstruction from power density data in limited view". A preprint of this paper is available on arXiv: https://arxiv.org/abs/2202.12370.

The python code used for the numerical examples in the paper "Jacobian of solutions to the conductivity equation in limited view". A preprint of this paper is available on arXiv: http://arxiv.org/abs/2207.03849.

This repository contains the code for the paper "Reinforcement learning of causal variables using mediation analysis" as accepted for AAAI-22.

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