Apoorva Sharma
Stanford University
deep neural networks
out-of-distribution
epistemic uncertainty
1
presentations
7
number of views
SHORT BIO
Apoorva Sharma is a PhD candidate in the Autonomous Systems Lab at Stanford University. He received an M.S. degree in Aeronautics and Astronautics from Stanford University in 2018, and a B.S. degree in Engineering from Harvey Mudd College in 2016. His research interests center around the application of machine learning models in control and sequential decision making applications, with a focus on Bayesian methods and quantifying uncertainty to enable safe application of machine learning systems in robot autonomy and decision making.
Presentations
Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks
Navid Azizan and 2 other authors