Alessandro Berlati

Ambiguity in Sequential Data: Predicting Uncertain Futures With Recurrent Models

Ambiguity is inherently present in many machine learning tasks, but especially for sequential models seldom accounted for, as most only output a single prediction. In this work we propose an extension of the Multiple Hypothesis Prediction (MHP) model to handle ambiguous predictions with sequential d