29 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.LG2021
Experiments on Properties of Hidden Structures of Sparse Neural Networks
Julian Stier, Harshil Darji, Michael Granitzer
Sparsity in the structure of Neural Networks can lead to less energy consumption, less memory usage, faster computation times on convenient hardware, and automated machine learning…
cs.LG2021★ 1 cited
Correlation Analysis between the Robustness of Sparse Neural Networks and their Random Hidden Structural Priors
M. Ben Amor, J. Stier, M. Granitzer
Deep learning models have been shown to be vulnerable to adversarial attacks. This perception led to analyzing deep learning models not only from the perspective of their performan…
cs.AI2019★ 29 cited
Analysing Neural Network Topologies: a Game Theoretic Approach
Julian Stier, Gabriele Gianini, Michael Granitzer +1
Artificial Neural Networks have shown impressive success in very different application cases. Choosing a proper network architecture is a critical decision for a network's success,…