amortized inference 1bayesian inference 1deep learning 1neural networks 1uncertainty quantification 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.ML2026
Neural Architectures for Amortized Bayesian Inference: Statistical Foundations and Empirical Assessments
Roy Shivam Ram Shreshtth, Arnab Hazra, Gourab Mukherjee
The paper examines how neural network architectures such as feedforward nets, Deep Sets, and Transformers can be used to amortize Bayesian inference, providing fast approximate pos…
stat.ME2026
Empirical Bayes Predictive Density Estimation under Covariate Shift in Large Imbalanced Linear Mixed Models
Abir Sarkar, Gourab Mukherjee, Keisuke Yano
We study empirical Bayes (EB) predictive density estimation in linear mixed models (LMMs) with large number of units, which induce a high dimensional random effects space. Focusing…
stat.ME2024
Semi-Supervised Learning of Noisy Mixture of Experts Models
Oh-Ran Kwon, Gourab Mukherjee, Jacob Bien
The mixture of experts (MoE) model is a versatile framework for predictive modeling that has gained renewed interest in the age of large language models. A collection of predictive…