Short Overview: A reproduce of the public talk as part of my PhD defense, which took place online on June 18th, ... In this work, we introduce a new technique that combines two popular methods to
An Uncertainty Estimation Framework For Probabilistic Object Detection - Topic Main Notes
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A reproduce of the public talk as part of my PhD defense, which took place online on June 18th, ... In this work, we introduce a new technique that combines two popular methods to
Action Notes
Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection, CoRL2022 Neural networks predictions are unreliable when the input sample is out of the training data distribution or corrupted by noise. Authors: Riedlinger, Tobias*; Rottmann, Matthias; Schubert, Marius; Gottschalk, Hanno Description: The majority of
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- Neural networks predictions are unreliable when the input sample is out of the training data distribution or corrupted by noise.
- Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection, CoRL2022
- Authors: Riedlinger, Tobias*; Rottmann, Matthias; Schubert, Marius; Gottschalk, Hanno Description: The majority of
- In this work, we introduce a new technique that combines two popular methods to
- A reproduce of the public talk as part of my PhD defense, which took place online on June 18th, ...
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![Object Detection as Probabilistic Set Prediction [ECCV2022]](https://i.ytimg.com/vi/UDWj7vNv970/mqdefault.jpg)
