no code implementations • 2 May 2022 • Maximilian Pintz, Joachim Sicking, Maximilian Poretschkin, Maram Akila
The success of deep learning (DL) fostered the creation of unifying frameworks such as tensorflow or pytorch as much as it was driven by their creation in return.
no code implementations • pproximateinference AABI Symposium 2021 • Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
One of the most commonly used approaches so far is Monte Carlo dropout, which is computationally cheap and easy to apply in practice.
1 code implementation • 23 Dec 2020 • Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
Despite of its importance for safe machine learning, uncertainty quantification for neural networks is far from being solved.
1 code implementation • 17 Dec 2020 • Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz
We propose two optimization schemes that make use of this: a modification of the Baum-Welch algorithm and a direct co-occurrence optimization.