2 papers
cs.LG2025
Assessing the Probabilistic Fit of Neural Regressors via Conditional Congruence
Spencer Young, Riley Sinema, Cole Edgren +3
While significant progress has been made in specifying neural networks capable of representing uncertainty, deep networks still often suffer from overconfidence and misaligned pred…
cs.LG2025
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
Spencer Young, Porter Jenkins, Longchao Da +2
Neural networks capable of accurate, input-conditional uncertainty representation are essential for real-world AI systems. Deep ensembles of Gaussian networks have proven highly ef…