Your Model is Wrong:
Robustness and misspecification in probabilistic modeling

Probabilistic modeling is a foundation of modern data analysis -- due in part to the flexibility and interpretability of these methods -- and has been applied to numerous application domains, such as the biological sciences, social and political sciences, engineering, and health care. However, any probabilistic model relies on assumptions that are necessarily a simplification of complex real-life processes; thus, any such model is inevitably misspecified in practice. In addition, as data set sizes grow and probabilistic models become more complex, applying a probabilistic modeling analysis often relies on algorithmic approximations, such as approximate Bayesian inference, numerical approximations, or data summarization methods. Thus in many cases, approximations used for efficient computation lead to fitting a misspecified model by design (e.g., variational inference). Importantly, in some cases, this misspecification leads to useful model inferences, but in others it may lead to misleading and potentially harmful inferences that may then be used for important downstream tasks for, e.g., making scientific inferences or policy decisions.

The goal of the workshop is to bring together researchers focused on methods, applications, and theory to outline some of the core problems in specifying and applying probabilistic models in modern data contexts along with current state-of-the-art solutions. Participants will leave the workshop with (i) exposure to recent advances in the field, (ii) an idea of the current major challenges in the field, and (iii) an introduction to methods meeting these challenges.

The workshop will take place on Tuesday December 14, 2021, virtually, at NeurIPS 2021.

Contact: robustbayesworkshop@gmail.com

• November 28, 2021: Schedule and accepted paper list is posted

• October 29, 2021: Important dates updated with camera ready, poster upload, and optional 3-minute upload deadlines

• August 10, 2021: Call for Papers posted!

Volunteer as a reviewer or discussant:

If you are interested in volunteering for the workshop as a reviewer or during the day-of event, please fill out the form at this link.

Previous related workshops:

• NeurIPS 2015: Bayesian Nonparametrics: The Next Generation

• NeurIPS 2016: Practical Bayesian Nonparametrics

• NeurIPS 2018: All of Bayesian Nonparametrics (Especially the Useful Bits)