I am looking for applications papers where people choose some task on which they will do Bayesian inferencing and graphical modeling, and then build an inference engine to infer latent parameters. And the focus should be applications rather than theory, meaning paper should appear more empirical than theoretical, it can be a mix of both also. Now the catch is I am looking for papers that are more on the engineering side for example supply chain optimization.

Conferences like NIPS, ICRA, AAAI, ICML have many papers where people build these inference engines. But most seem to be in vision area for example this. I am looking for applications on engineering problems rather than computer science problems.

I know this may sound like a trivial question on this site but I am new to probability programming domain. I am having a hard time to find one. It may be I am looking at the wrong conferences or in the wrong way. But it would be helpful if I can get some helpful tips here rather than downvotes.

I want to get an idea of what kind of recent research people are doing so that I can make my own plan. If you cannot find papers on the engineering side then you could cite some on economics or finance side.


You can check out the archives of StanCon - there's a lot of great applied Bayesian work with source code (obviously using the Stan language).

There is for example: Modelling demand for gas or resonance ultrasound spectroscopy.


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