24 citations · 52 across the 13 of their papers we have counts for
3 papers · 1 filter
You can have your ensemble and run it too -- Deep Ensembles Spread Over Time
Isak Meding, Alexander Bodin, Adam Tonderski +3
Ensembles of independently trained deep neural networks yield uncertainty estimates that rival Bayesian networks in performance. They also offer sizable improvements in terms of pr…
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks
Ziliang Xiong, Arvi Jonnarth, Abdelrahman Eldesokey +3
Computer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty. We study regression from images to parameter values and here it…
Raw or Cooked? Object Detection on RAW Images
William Ljungbergh, Joakim Johnander, Christoffer Petersson +1
Images fed to a deep neural network have in general undergone several handcrafted image signal processing (ISP) operations, all of which have been optimized to produce visually ple…