David Peer

Trans. Mach. Learn. Res., 2022

Momentum Capsule Networks.

[BibT_eX]

[DOI]

Josef Gugglberger

Trans. Mach. Learn. Res., 2022

Greedy-layer pruning: Speeding up transformer models for natural language processing.

[BibT_eX]

[DOI]

Stefan Engl

Pattern Recognit. Lett., 2022

Improving 3D Point Cloud Reconstruction with Dynamic Tree-Structured Capsules.

[BibT_eX]

[DOI]

Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022

Affordance detection with Dynamic-Tree Capsule Networks.

[BibT_eX]

[DOI]

Proceedings of the 21st IEEE-RAS International Conference on Humanoid Robots, 2022

2021

conflicting_bundle.py - A python module to identify problematic layers in deep neural networks.

[BibT_eX]

[DOI]

Softw. Impacts, 2021

Limitation of capsule networks.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2021

Arguments for the unsuitability of convolutional neural networks for non-local tasks.

[BibT_eX]

[DOI]

Neural Networks, 2021

Greedy Layer Pruning: Decreasing Inference Time of Transformer Models.

[BibT_eX]

[DOI]

Stefan Engl

CoRR, 2021

Auto-tuning of Deep Neural Networks by Conflicting Layer Removal.

[BibT_eX]

[DOI]

CoRR, 2021

Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Training Deep Capsule Networks with Residual Connections.

[BibT_eX]

[DOI]

Josef Gugglberger

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Resilient Techniques Against Disruptions of Volatile Cloud Resources.

[BibT_eX]

[DOI]

Proceedings of the Guide to Disaster-Resilient Communication Networks, 2020

2019

Limitations of routing-by-agreement based capsule networks.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Training Deep Capsule Networks.

[BibT_eX]

[DOI]