543 citations · 578 across the 9 of their papers we have counts for
3 papers · 1 filter
Uncertainty Aware AI ML: Why and How
Lance Kaplan, Federico Cerutti, Murat Sensoy +2
This paper argues the need for research to realize uncertainty-aware artificial intelligence and machine learning (AI\&ML) systems for decision support by describing a number of mo…
Probabilistic Logic Programming with Beta-Distributed Random Variables
Federico Cerutti, Lance Kaplan, Angelika Kimmig +1
We enable aProbLog---a probabilistic logical programming approach---to reason in presence of uncertain probabilities represented as Beta-distributed random variables. We achieve th…
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy, Lance Kaplan, Melih Kandemir
Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to m…