Accurate Prediction and Uncertainty Estimation using Decoupled Prediction Interval Networks

no code implementations • 19 Feb 2022 • Kinjal Patel, Steven Waslander

We compare the proposed method with current state-of-the-art uncertainty quantification algorithms on synthetic datasets and UCI benchmarks, reducing the error in the predictions by 23 to 34% while maintaining 95% Prediction Interval Coverage Probability (PICP) for 7 out of 9 UCI benchmark datasets.

Active Learning Uncertainty Quantification

A Spiking Neural Network for Image Segmentation

no code implementations • 16 Jun 2021 • Kinjal Patel, Eric Hunsberger, Sean Batir, Chris Eliasmith

We explore the advantages of regularizing firing rates of Loihi neurons for converting ANN to SNN with minimum accuracy loss and optimized energy consumption.

Benchmarking Image Segmentation +1