We are happy to announce that the Differentiable and Probabilistic Programming for Fundamental Physics program includes a three day workshop. The workshop will contain talks about recent advancements in differentiable programming (DP) and probabilistic programming in the context of Physical Sciences. The workshop's diverse set of invited speakers will cover DP/ProbProg users and experts, toolmakers and authors of promising technologies. The workshop aims to explore the potential science impact of DP/ProbProg and to understand the steps towards, and challenges of, a successful implementation of these paradigms in fundamental physics.
Topics to be covered in the workshop include:
* Exploiting Differentiable and Probabilistic Programming For Scientific Machine Learning
* Compilers, Languages & Toolchains
* Gradient-Estimation & Relaxation Techniques
* Automating Inference with Astro-and Particle Physics Simulators
* Adoption and Scaling strategies for Big Science: Recent Application and Success Stories
Please note that the number of seats to attend the workshop is limited. You will be informed ahead of the Topical Workshop whether you were selected for participation.
If you are invited for week 4 of the MIAPbP Program "Differentiable and Probabilistic Programming for Fundamental Physics", you are automatically registered for the Topical Workshop and abstracts can be submitted without registering via indico.
We would like to encourage undergraduate and graduate students as well as early career researchers to share their experience in the field. The short talk session and the poster session are designed to allow exchanging of early implementation ideas, learning about ongoing activities and networking.
