65 citations · 78 across the 7 of their papers we have counts for
3 papers · 1 filter
Temporal Predictive Multiplicity: Equally Accurate Time Series Models Yield Different Forecast Trajectories
Emanuele Albini, Francesca Toni, Saumitra Mishra +1
Models with near-identical predictive performance can yield substantially different predictions, a phenomenon known as predictive multiplicity. Prior work has mostly studied this a…
Entropic Projection Alignment: Estimating, Explaining, and Improving Model Performance Under Distribution Shift
Salim I. Amoukou, Emanuele Albini, Tom Bewley +2
We propose a unified framework for addressing three key challenges of distribution shift: (1) estimating a model's performance on an unlabeled target domain, (2) explaining the shi…
ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values
Tom Bewley, Salim I. Amoukou, Emanuele Albini +2
Changes in input distribution can induce shifts in the average predictions of machine learning models. Such prediction shifts may impact downstream business outcomes (e.g. a bank's…