2 papers
stat.CO2025
Bayesian Neural Networks vs. Mixture Density Networks: Theoretical and Empirical Insights for Uncertainty-Aware Nonlinear Modeling
Riddhi Pratim Ghosh, Ian Barnett
This paper investigates two prominent probabilistic neural modeling paradigms: Bayesian Neural Networks (BNNs) and Mixture Density Networks (MDNs) for uncertainty-aware nonlinear r…
stat.ME2024
Two-Sample Hypothesis Testing for Large Random Graphs of Unequal Size
Xin Jin, Kit Chan, Ian Barnett +1
Two-sample hypothesis testing for large graphs is popular in cognitive science, probabilistic machine learning and artificial intelligence. While numerous methods have been propose…