66 citations · 77 across the 4 of their papers we have counts for
4 papers
Tutorial on Deep Learning for Human Activity Recognition
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Activity recognition systems that are capable of estimating human activities from wearable inertial sensors have come a long way in the past decades. Not only have state-of-the-art…
Stochastic Training is Not Necessary for Generalization
Jonas Geiping, Micah Goldblum, Phillip E. Pope +2
It is widely believed that the implicit regularization of SGD is fundamental to the impressive generalization behavior we observe in neural networks. In this work, we demonstrate t…
Improving Deep Learning for HAR with shallow LSTMs
Marius Bock, Alexander Hoelzemann, Michael Moeller +1
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning arc…
Training or Architecture? How to Incorporate Invariance in Neural Networks
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner +2
Many applications require the robustness, or ideally the invariance, of a neural network to certain transformations of input data. Most commonly, this requirement is addressed by e…