217 citations · 323 across the 12 of their papers we have counts for
4 papers · 1 filter
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth
Edi Muškardin, Martin Tappler, Ingo Pill +2
We examine the assumption that the hidden-state vectors of recurrent neural networks (RNNs) tend to form clusters of semantically similar vectors, which we dub the clustering hypot…
Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks
Thomas Grandits, Simone Pezzuto, Francisco Sahli Costabal +4
Electroanatomical maps are a key tool in the diagnosis and treatment of atrial fibrillation. Current approaches focus on the activation times recorded. However, more information ca…
On the estimation of the Wasserstein distance in generative models
Thomas Pinetz, Daniel Soukup, Thomas Pock
Generative Adversarial Networks (GANs) have been used to model the underlying probability distribution of sample based datasets. GANs are notoriuos for training difficulties and th…
Fast Decomposable Submodular Function Minimization using Constrained Total Variation
K S Sesh Kumar, Francis Bach, Thomas Pock
We consider the problem of minimizing the sum of submodular set functions assuming minimization oracles of each summand function. Most existing approaches reformulate the problem a…