3 papers
stat.CO2025
SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era
Elizaveta Semenova, Alisa Sheinkman, Timothy James Hitge +2
Surrogate models are widely used to approximate complex systems across science and engineering to reduce computational costs. Despite their widespread adoption, the field lacks sta…
cs.LG2025
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
Alisa Sheinkman, Sara Wade
As modern neural networks get more complex, specifying a model with high predictive performance and sound uncertainty quantification becomes a more challenging task. Despite some p…
stat.ML2025
Variational Bayesian Bow tie Neural Networks with Shrinkage
Alisa Sheinkman, Sara Wade
Despite the dominant role of deep models in machine learning, limitations persist, including overconfident predictions, susceptibility to adversarial attacks, and underestimation o…