In recent years, there have been numerous advances in approximate inference methods, which have enabled Bayesian inference in increasingly challenging scenarios involving complex probabilistic models and large datasets. The 5th Symposium on Advances in Approximate Bayesian Inference (AABI) will discuss this impact of Bayesian inference, connecting both variational and Monte Carlo methods with other fields. We encourage submissions that relate Bayesian inference to the fields of deep learning, reinforcement learning, causal inference, decision processes, Bayesian compression, or differential privacy, among others. We also encourage submissions that contribute to connecting different approximate inference methods.
For the call for papers and submission instructions, click here. This year we will be running an additional fast-track call for authors to present papers accepted at ICLR 2023, ICML 2023, AISTATS 2023, and UAI 2023, as well as JMLR and TMLR in 2023. Both the regular and fast-track submission portals are now closed!
Registration for in-person attendance is free but will be limited. Click here to register! All accepted papers must have at least one author attending in person. We will request an email confirmation from all registered attendees in early July. If you are unable to register, feel free to sign up on the waiting list. We will contact you if more slots become available. Given the limited seats, please cancel your registration if you know you will not be able to attend in-person.
This symposium is a continuation of past years events: