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Shireen Kudukkil Manchingal

4 accepted papers

2026

Uncertainty-Aware Autonomous Vehicles: Predicting the Road Ahead

ICRA 2026poster

Autonomous Vehicle (AV) perception systems have advanced rapidly in recent years, providing vehicles with the ability to accurately interpret their environment. Perception systems remain susceptible to errors caused by overly-confident predictions in the case of rare events or out-of-sample data. Th…

2025

A Unified Evaluation Framework for Epistemic Predictions

AISTATS 2025poster

Predictions of uncertainty-aware models are diverse, ranging from single point estimates (often averaged over prediction samples) to predictive distributions, to set-valued or credal-set representations. We propose a novel unified evaluation framework for uncertainty-aware classifiers, applicable to…

Cited by 0SourceScholar
2025

Random-Set Neural Networks

ICLR 2025poster

Machine learning is increasingly deployed in safety-critical domains where erroneous predictions may lead to potentially catastrophic consequences, highlighting the need for learning systems to be aware of how confident they are in their own predictions: in other words, 'to know when they do not kno…

Cited by 1SourcePDFScholar
2024

Credal Deep Ensembles for Uncertainty Quantification

NeurIPS 2024poster

This paper introduces an innovative approach to classification called Credal Deep Ensembles (CreDEs), namely, ensembles of novel Credal-Set Neural Networks (CreNets). CreNets are trained to predict a lower and an upper probability bound for each class, which, in turn, determine a convex set of proba…

Cited by 3SourcePDFScholar