Greedy-layer Pruning: Speeding up Transformer Models for Natural Language Processing D Peer, S Stabinger, S Engl, A Rodriguez-Sanchez
Pattern Recognition Letters, 2022, 2022
42 2022 Limitation of capsule networks D Peer, S Stabinger, A Rodriguez-Sanchez
Pattern Recognition Letters 144, 68 - 74, 2021
31 2021 Increasing the adversarial robustness and explainability of capsule networks with D Peer, S Stabinger, A Rodriguez-Sanchez
https://arxiv.org/abs/1812.09707, 2019
25 * 2019 Evaluating the progress of deep learning for visual relational concepts S Stabinger, D Peer, J Piater, A Rodríguez-Sánchez
Journal of Vision 21 (11), 8-8, 2021
21 2021 Training Deep Capsule Networks with Residual Connections J Gugglberger, D Peer, A Rodriguez-Sanchez
International Conference on Artificial Neural Networks (ICANN) 30, 2021
18 2021 Limitations of routing-by-agreement based capsule networks D Peer, S Stabinger, A Rodriguez-Sanchez
arXiv preprint arXiv:1905.08744, 2019
12 2019 Increasing the adversarial robustness and explainability of capsule networks with D Peer, S Stabinger, A Rodriguez-Sanchez
arXiv preprint arXiv:1812.09707, 2018
12 2018 Arguments for the unsuitability of convolutional neural networks for non-local tasks S Stabinger, D Peer, A Rodríguez-Sánchez
Neural Networks 142, 171-179, 2021
9 2021 Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks D Peer, S Stabinger, A Rodriguez-Sanchez
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
8 2021 Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization D Peer, B Keulen, S Stabinger, J Piater, A Rodríguez-Sánchez
Transactions on Machine Learning Research (TMLR), 2022
6 2022 Resilient techniques against disruptions of volatile cloud resources S Ristov, T Fahringer, D Peer, TP Pham, M Gusev, C Mas-Machuca
Guide to Disaster-Resilient Communication Networks, 379-400, 2020
5 2020 DEEP LEARNING FOR REAL-TIME AVALANCHE DETECTION IN WEBCAM IMAGES J Fox, A Siebenbrunner, S Reitinger, D Peer, A Rodrıguez-Sánchez
4 2023 Momentum capsule networks J Gugglberger, D Peer, A Rodríguez-Sánchez
arXiv preprint arXiv:2201.11091, 2022
4 2022 Auto-tuning of deep neural networks by conflicting layer removal D Peer, S Stabinger, A Rodriguez-Sanchez
arXiv preprint arXiv:2103.04331, 2021
4 2021 conflicting_bundle. py—A python module to identify problematic layers in deep neural networks D Peer, S Stabinger, A Rodríguez-Sánchez
Software Impacts, 100053, 2021
4 2021 Automating Avalanche Detection in Ground-Based Photographs with Deep Learning J Fox, A Siebenbrunner, S Reitinger, D Peer, A Rodrı́guez-Sánchez
Available at SSRN 4537379, 2023
3 2023 ANLS*--A Universal Document Processing Metric for Generative Large Language Models D Peer, P Schöpf, V Nebendahl, A Rietzler, S Stabinger
arXiv preprint arXiv:2402.03848, 2024
2 2024 Improving 3D Point Cloud Reconstruction with Dynamic Tree-Structured Capsules C Engelhardt, J Mittelberger, D Peer, S Stabinger, A Rodríguez-Sánchez
2022 IEEE 5th International Conference on Image Processing Applications and …, 2022
1 2022 Affordance detection with Dynamic-Tree Capsule Networks A Rodríguez-Sánchez, S Haller-Seeber, D Peer, C Engelhardt, ...
2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids …, 2022
1 2022 Training of Feedforward Networks Fails on a Simple Parity-Task S Stabinger, D Peer, A Rodríguez-Sánchez, A Rodriguez
NeurIPS 2020 pre-registration workshop, 2020
2020 
Antonio Rodriguez-SanchezAssociate Professor, University of InnsbruckПодтвержден адрес электронной почты в домене uibk.ac.at