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20212024
most citedA Survey of Uncertainty in Deep Neural Networks

242 citations · 277 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024★ 1 cited

Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry

Ferdinand Rewicki, Jakob Gawlikowski, Julia Niebling +1

The detection of abnormal or critical system states is essential in condition monitoring. While much attention is given to promptly identifying anomalies, a retrospective analysis…

cs.LG2022★ 33 cited

The Unreasonable Effectiveness of Deep Evidential Regression

Nis Meinert, Jakob Gawlikowski, Alexander Lavin

There is a significant need for principled uncertainty reasoning in machine learning systems as they are increasingly deployed in safety-critical domains. A new approach with uncer…

cs.LG2021★ 242 cited

A Survey of Uncertainty in Deep Neural Networks

Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali +11

Due to their increasing spread, confidence in neural network predictions became more and more important. However, basic neural networks do not deliver certainty estimates or suffer…

cs.LG2021

Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Trajectories

Sandeep Kumar Singh, Jaya Shradha Fowdur, Jakob Gawlikowski +1

Understanding and representing traffic patterns are key to detecting anomalous trajectories in the transportation domain. However, some trajectories can exhibit heterogeneous maneu…

cs.LG2021★ 1 cited

Out-of-distribution detection in satellite image classification

Jakob Gawlikowski, Sudipan Saha, Anna Kruspe +1

In satellite image analysis, distributional mismatch between the training and test data may arise due to several reasons, including unseen classes in the test data and differences…