| title | COST INTERACT - DiffeRT2d: A Differentiable Ray Tracing Python Framework for Radio Propagation | ||||||
|---|---|---|---|---|---|---|---|
| categories |
|
||||||
| tags |
|
||||||
| website | https://eertmans.be/DiffeRT2d/ | ||||||
| github | jeertmans/DiffeRT2d | ||||||
| image |
|
||||||
| permalink | /posts/cost-interact-june-2024-differt2d/ | ||||||
| redirect_from | /posts/cost-interact-june-2024-differt2d-presentation/ | ||||||
| description | Presentation of the DiffeRT2d toolbox at the COST INTERACT meeting in Helsinki, Finland. |
In the preparation of our submission to the Journal of Open Source Software, I presented the DiffeRT2d Python library at the COST INTERACT meeting, held in Helsinki. This toolbox was used to define and train a Machine Learning model to help tracing paths faster, that we documented in another document presented during this meeting.
Moreover, this toolbox implements both our Min-Path-Tracing method {% cite Eert2303:Min %} and our smoothing technique {% cite Eert2403:Fully %}.
{% include slides.html url="/assets/slides/2024-06-16-helsinki-differt2d-presentation/slides.html" skip_manim_citation=true %}
{% bibliography --cited %}
Available on GitHub:
jeertmans/DiffeRT2d@papers/joss/slides.md{: .filepath}.