David Peer

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 21

Top Topics

Back Propagation

Endoscopic Images

Training Patterns

Top Venues

Pattern Recognit. Lett.

Trans. Mach. Learn. Res.

Publications

David Peer, Philemon Schöpf, Volckmar Nebendahl, Alexander Rietzler, Sebastian Stabinger
ANLS* - A Universal Document Processing Metric for Generative Large Language Models. CoRR (2024)
Antonio Jose Rodríguez-Sánchez, Simon Haller-Seeber, David Peer, Chris Engelhardt, Jakob Mittelberger, Matteo Saveriano
Affordance detection with Dynamic-Tree Capsule Networks. Humanoids (2022)
Josef Gugglberger, Antonio Jose Rodríguez-Sánchez, David Peer
Momentum Capsule Networks. Trans. Mach. Learn. Res. 2022 (2022)
Antonio Jose Rodríguez-Sánchez, Simon Haller-Seeber, David Peer, Chris Engelhardt, Jakob Mittelberger, Matteo Saveriano
Affordance detection with Dynamic-Tree Capsule Networks. CoRR (2022)
Josef Gugglberger, David Peer, Antonio Jose Rodríguez-Sánchez
Momentum Capsule Networks. CoRR (2022)
David Peer, Bart Keulen, Sebastian Stabinger, Justus H. Piater, Antonio Jose Rodríguez-Sánchez
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization. CoRR (2022)
Chris Engelhardt, Jakob Mittelberger, David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Improving 3D Point Cloud Reconstruction with Dynamic Tree-Structured Capsules. IPAS (2022)
David Peer, Bart Keulen, Sebastian Stabinger, Justus H. Piater, Antonio Jose Rodríguez-Sánchez
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization. Trans. Mach. Learn. Res. 2022 (2022)
David Peer, Sebastian Stabinger, Stefan Engl, Antonio Jose Rodríguez-Sánchez
Greedy-layer pruning: Speeding up transformer models for natural language processing. Pattern Recognit. Lett. 157 (2022)
Sebastian Stabinger, David Peer, Antonio Jose Rodríguez-Sánchez
Arguments for the Unsuitability of Convolutional Neural Networks for Non-Local Tasks. CoRR (2021)
Sebastian Stabinger, David Peer, Antonio Jose Rodríguez-Sánchez
Arguments for the unsuitability of convolutional neural networks for non-local tasks. Neural Networks 142 (2021)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
conflicting_bundle.py - A python module to identify problematic layers in deep neural networks. Softw. Impacts 7 (2021)
Josef Gugglberger, David Peer, Antonio Jose Rodríguez-Sánchez
Training Deep Capsule Networks with Residual Connections. CoRR (2021)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Limitation of capsule networks. Pattern Recognit. Lett. 144 (2021)
Josef Gugglberger, David Peer, Antonio Jose Rodríguez-Sánchez
Training Deep Capsule Networks with Residual Connections. ICANN (1) (2021)
David Peer, Sebastian Stabinger, Stefan Engl, Antonio Jose Rodríguez-Sánchez
Greedy Layer Pruning: Decreasing Inference Time of Transformer Models. CoRR (2021)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks. WACV (2021)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Auto-tuning of Deep Neural Networks by Conflicting Layer Removal. CoRR (2021)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks. CoRR (2020)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Limitations of routing-by-agreement based capsule networks. CoRR (2019)
David Peer, Sebastian Stabinger, Antonio Jose Rodríguez-Sánchez
Training Deep Capsule Networks. CoRR (2018)