About

On Friday September 20th, 2019 as part of IBM Research's AI week, we will be hosting the first workshop on Practical Bayesian Methods for Big Data.

Bayesian methods have long benefited from their ability to both coherently represent uncertainty and incorporate prior knowledge, but have traditionally struggled to scale to both large data and large models. Deep learning approaches empirically demonstrate the benefits of learning large over-parameterized models from large data, but struggle with producing well calibrated uncertainties. Research attempting to both scale up Bayesian methods and combine the benefits of either paradigm has recently garnered significant attention. Examples include deep generative models and Bayesian neural networks. This workshop will advance and accelerate research on statistical underpinnings of methods at this intersection, including recent advances in Bayesian approaches for learning neural network based models, deep learning methods for Bayesian modeling, methods for scaling up Bayesian inference to large models and data, and use of classical statistical tools for measuring robustness and reliability of deep learning models.

We invite researchers to submit work in (but not limited to) the following areas:

• Bayesian approaches for learning neural network based models.
• Advances in deep generative modeling.
• Deep learning methods for Bayesian modeling.
• Methods for scaling up Bayesian inference to large models and data.
• Methods for measuring robustness and reliability of statistical models.

Submissions

Submission can be made via an EasyChair submission. The submission should be in the form of an extended abstract and should not exceed 3 pages (excluding references) in PDF format using NeurIPS style. Submissions of new ideas, recently published works and/or extension of existing works are welcome. Parallel submissions or submissions of under-review works are also permitted. Author names do not need to be anonymized. Submission will be accepted as contributed 15-minute talks or poster presentations. The final versions will be posted on the workshop website (and are archival but do not constitute a proceeding). 

Key Dates

• Submission due: 09/11/2019
• Notification to Submitters: 09/15/2019
• Meeting Date: 09/20/2019

Attendance

For each accepted paper or poster, at least one author must attend the workshop and present the paper/poster.