3 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…
quant-ph2025
Characterizing errors in parameter estimation by local measurements
Riddhi Ghosh, Alexei Gilchrist, Daniel Burgarth
The indirect estimation of couplings in quantum dynamics relies on the measurement of the spectrum and the overlap of eigenvectors with some reference states. This data can be obta…
stat.ME2025
Generalized Tree-Informed Mixed Model Regression
Jeremiah Allis, Xin Jin, Riddhi Ghosh
The standard regression tree method applied to observations within clusters poses both methodological and implementation challenges. Effectively leveraging these data requires meth…