2020
Scalable Uncertainty for Computer Vision With Functional Variational Inference
CVPR 2020poster
As Deep Learning continues to yield successful applications in Computer Vision, the ability to quantify all forms of uncertainty is a paramount requirement for its safe and reliable deployment in the real-world. In this work, we leverage the formulation of variational inference in function space, wh…