Computing persistent homology under random projection
Karthikeyan Natesan Ramamurthy, Kush R. Varshney, et al.
SSP 2014
This tutorial presents an open source Python package (https://github.com/IBM/UQ360) named Uncertainty Quantification 360 (UQ360), a toolkit that provides a broad range of capabilities for quantifying, evaluating, improving, and communicating uncertainty in the AI application development lifecycle. We will first introduce the concepts in uncertainty quantification through an interactive experience (http://uq360.mybluemix.net) followed by use cases with different quantification algorithms and evaluation metrics. The hands-on experience gained from tutorial will aid researchers and developers in producing and evaluating high-quality uncertainties from AI models in an efficient manner.
Karthikeyan Natesan Ramamurthy, Kush R. Varshney, et al.
SSP 2014
Abhinav Nagpal, Riddhiman Dasgupta, et al.
CODS-COMAD 2022
Kristen A. Severson, Soumya Ghosh, et al.
AAAI 2019
Neelamadhav Gantayat, Prateeti Mohapatra
CODS-COMAD 2022