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06/13/2022
Multi-Agent Neural Rewriter for Vehicle Routing with Limited Disclosure of Costs
We interpret solving the multi-vehicle routing problem as a team Markov ...
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04/29/2022
Tailored Uncertainty Estimation for Deep Learning Systems
Uncertainty estimation bears the potential to make deep learning (DL) sy...
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06/10/2021
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
Many machine learning applications can benefit from simulated data for s...
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04/19/2021
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation
Data-driven sensor interpretation in autonomous driving can lead to high...
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04/15/2021
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving
Artificial intelligence for autonomous driving must meet strict requirem...
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03/29/2021
Supporting verification of news articles with automated search for semantically similar articles
Fake information poses one of the major threats for society in the 21st ...
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01/08/2021
Approaching Neural Network Uncertainty Realism
Statistical models are inherently uncertain. Quantifying or at least upp...
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01/07/2021
A Novel Regression Loss for Non-Parametric Uncertainty Optimization
Quantification of uncertainty is one of the most promising approaches to...
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12/23/2020
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties
Quantification of uncertainty is one of the most promising approaches to...
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12/17/2020
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
We propose DenseHMM - a modification of Hidden Markov Models (HMMs) that...
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07/10/2020
Characteristics of Monte Carlo Dropout in Wide Neural Networks
Monte Carlo (MC) dropout is one of the state-of-the-art approaches for u...
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07/09/2018
