IEEE

Bayesian Optimization for Sparse Neural Networks With Trainable Activation Functions

Abstract: In the literature on deep neural networks, there is considerable interest in developing activation functions that can enhance neural network performance. In recent years, there has been ...
The Lancet

Impact of the national steps challenge physical activity programme on obesity and type 2 diabetes prevalence in Singapore to 2050: simulation-based forecasting analysis

Physical activity programmes such as the NSC can help mitigate rising obesity and T2DM prevalence when implemented at the population level, as seen in Singapore. However, their success depends on ...
InfoQ

Google Researchers Propose Bayesian Teaching Method for Large Language Models

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by ...
appliedclinicaltrialsonline

ACT Brief: Bayesian Implementation, Women in Statistics, and FDA Tightens Gene Therapy Standards

In today's ACT Brief, we explore the operational capabilities clinical teams need to implement Bayesian trial designs, why gender diversity strengthens data science across drug development, and the ...
IEEE

Constrained Bayesian Optimization: A Review

Abstract: Bayesian optimization is a sequential optimization method that is particularly well suited for problems with limited computational budgets involving expensive and non-convex black-box ...