1k citations · 3.7k across the 13 of their papers we have counts for
16 papers
The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual Explanations
Anselm Haselhoff, Kevin Trelenberg, Fabian Küppers +1
Visual counterfactual explanation (CF) methods modify image concepts, e.g, shape, to change a prediction to a predefined outcome while closely resembling the original query image.…
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection
Fabian Küppers, Jonas Schneider, Anselm Haselhoff
Reliable spatial uncertainty evaluation of object detection models is of special interest and has been subject of recent work. In this work, we review the existing definitions for…
Confidence Calibration for Object Detection and Segmentation
Fabian Küppers, Anselm Haselhoff, Jan Kronenberger +1
Calibrated confidence estimates obtained from neural networks are crucial, particularly for safety-critical applications such as autonomous driving or medical image diagnosis. Howe…
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Fabian Küppers, Jan Kronenberger, Jonas Schneider +1
Modern neural networks have found to be miscalibrated in terms of confidence calibration, i.e., their predicted confidence scores do not reflect the observed accuracy or precision.…
On Feature Relevance Uncertainty: A Monte Carlo Dropout Sampling Approach
Kai Fischer, Jonas Schneider
Understanding decisions made by neural networks is key for the deployment of intelligent systems in real world applications. However, the opaque decision making process of these sy…
Dota 2 with Large Scale Deep Reinforcement Learning
OpenAI, :, Christopher Berner +24
On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game. The game of Dota 2 presents novel challenges for AI systems such as lo…