The Department of Atomic Energy (DAE) and the National Board for Higher Mathematics (NBHM) are jointly sponsoring a two-day seminar on "Research Perspective on Probabilistic Model Construction and Markov Chain Monte Carlo (MCMC) with Bayesian Deep Le

The Department of Atomic Energy (DAE) and the National Board for Higher Mathematics (NBHM) are jointly sponsoring a two-day seminar on "Research Perspective on Probabilistic Model Construction and Markov Chain Monte Carlo (MCMC) with Bayesian Deep Le

ABOUT

THE SEMINAR

The seminar aims to address the limitations of traditional deep learning models in representing uncertainty and leveraging the tools of probability theory, specifically in the context of medical data. Recent advancements in combining Bayesian approaches with deep learning have started to bridge this gap. The intersection of these two fields has garnered significant interest from the community in recent years, leading to the introduction of new deep learning models that incorporate Bayesian techniques.

This seminar will serve as a platform to explore the latest ideas and advancements in using Bayesian approaches in deep learning and applying deep learning tools to Bayesian modeling. The primary focus will be on the applications of Bayesian deep learning in the field of machine learning, with a specific emphasis on medical data.

BENEFICIARIES

Students - UG and PG, Faculty Members, Research Scholars,

Medical Researches