49 citations · 157 across the 21 of their papers we have counts for
3 papers · 1 filter
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
Joachim Sicking, Maximilian Pintz, Maram Akila +1
We propose DenseHMM - a modification of Hidden Markov Models (HMMs) that allows to learn dense representations of both the hidden states and the observables. Compared to the standa…
Towards Map-Based Validation of Semantic Segmentation Masks
Laura von Rueden, Tim Wirtz, Fabian Hueger +2
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness. We propose to validate machine learning models for self-driving vehicles not…
Characteristics of Monte Carlo Dropout in Wide Neural Networks
Joachim Sicking, Maram Akila, Tim Wirtz +2
Monte Carlo (MC) dropout is one of the state-of-the-art approaches for uncertainty estimation in neural networks (NNs). It has been interpreted as approximately performing Bayesian…