3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.LG2026
On the QUEST for Uncertainty Quantification via Highest Density Regions
Sam Goring, Tom Kuipers, Nicola Paoletti +1
Uncertainty quantification (UQ) is essential for reliable decision-making in safety-critical applications in probabilistic machine learning. For regression problems, dominant scala…
cs.LO2024★ 2 cited
Verifiably Robust Conformal Prediction
Linus Jeary, Tom Kuipers, Mehran Hosseini +1
Conformal Prediction (CP) is a popular uncertainty quantification method that provides distribution-free, statistically valid prediction sets, assuming that training and test data…
cs.MA2024★ 3 cited
Conformal Off-Policy Prediction for Multi-Agent Systems
Tom Kuipers, Renukanandan Tumu, Shuo Yang +3
Off-Policy Prediction (OPP), i.e., predicting the outcomes of a target policy using only data collected under a nominal (behavioural) policy, is a paramount problem in data-driven…