Training Deep Capsule Networks. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (CoRR, 2018)

Limitations of routing-by-agreement based capsule networks. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (CoRR, 2019)

Resilient Techniques Against Disruptions of Volatile Cloud Resources. - Sasko Ristov; Thomas Fahringer; David Peer; Thanh-Phuong Pham; Marjan Gusev; Carmen Mas Machuca (Guide to Disaster-Resilient Communication Networks, 2020)

Training Deep Capsule Networks with Residual Connections. - Josef Gugglberger; David Peer; Antonio Jose Rodríguez-Sánchez (ICANN (1), 2021)

Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (WACV, 2021)

Auto-tuning of Deep Neural Networks by Conflicting Layer Removal. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (CoRR, 2021)

Greedy Layer Pruning: Decreasing Inference Time of Transformer Models. - David Peer; Sebastian Stabinger; Stefan Engl; Antonio Jose Rodríguez-Sánchez (CoRR, 2021)

Arguments for the unsuitability of convolutional neural networks for non-local tasks. - Sebastian Stabinger; David Peer; Antonio Jose Rodríguez-Sánchez (Neural Networks, 2021)

Limitation of capsule networks. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (Pattern Recognit. Lett., 2021)

conflicting_bundle.py - A python module to identify problematic layers in deep neural networks. - David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (Softw. Impacts, 2021)

Affordance detection with Dynamic-Tree Capsule Networks. - Antonio Jose Rodríguez-Sánchez; Simon Haller-Seeber; David Peer; Chris Engelhardt; Jakob Mittelberger; Matteo Saveriano (Humanoids, 2022)

Improving 3D Point Cloud Reconstruction with Dynamic Tree-Structured Capsules. - Chris Engelhardt; Jakob Mittelberger; David Peer; Sebastian Stabinger; Antonio Jose Rodríguez-Sánchez (IPAS, 2022)

Greedy-layer pruning: Speeding up transformer models for natural language processing. - David Peer; Sebastian Stabinger; Stefan Engl; Antonio Jose Rodríguez-Sánchez (Pattern Recognit. Lett., 2022)

Momentum Capsule Networks. - Josef Gugglberger; Antonio Jose Rodríguez-Sánchez; David Peer (Trans. Mach. Learn. Res., 2022)

Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization. - David Peer; Bart Keulen; Sebastian Stabinger; Justus H. Piater; Antonio Jose Rodríguez-Sánchez (Trans. Mach. Learn. Res., 2022)

ANLS* - A Universal Document Processing Metric for Generative Large Language Models. - David Peer; Philemon Schöpf; Volckmar Nebendahl; Alexander Rietzler; Sebastian Stabinger (CoRR, 2024)