Wissenschaftliche Publikationen

2021

M. Fey, J. E. Lenssen, F. Weichert and J. Leskovec, "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" , International Conference on Machine Learning (ICML) 2021 (accepted for publication), 2021.
T. Harweg, D. Bachmann and F. Weichert, "Agent-based Simulation of Pedestrian Dynamics for Exposure Time Estimationin Epidemic Risk Assessment" , Journal of Public Health, 2021.
 Link https://doi.org/10.1007/s10389-021-01489-y

2020

M. D. Jedrusiak and F. Weichert, "A Deep Learning Approach for Denoising Air-Coupled Ultrasonic Responds Data" , International Journal of Artificial Intelligence and Applications (IJAIA), vol. 11, no. 4, pp. 15-28, 2020.
 PDF Link
M. Kleineberg, M. Fey and F. Weichert, "Adversarial Generation of Continuous Implicit Shape Representations" in Eurographics, 2020.
 PDF Link
K. Wüstefeld and F. Weichert, "An Automated Rapid Test for Viral Nanoparticles Based on Spatiotemporal Deep Learning" , IEEE Sensors, pp. 1-4, 2020.
 PDF Link 10.1109/SENSORS47125.2020.9278935
T. Harweg, A. Peter, D. Bachmann and F. Weichert, CNN-Based Deep Architecture for Health Monitoring of Civil and Industrial Structures using UAVs: 6th International Electronic Conference on Sensors and Applications.
 PDF https://doi.org/10.3390/ecsa-6-06640
M. Fey, J. E. Lenssen, C. Morris, J. Masci and N. Kriege, "Deep Graph Matching Consensus" in International Conference on Learning Representations (ICLR), 2020.
 PDF Link
J. E. Lenssen, C. Osendorfer and J. Masci, "Deep Iterative Surface Normal Estimation" in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
 PDF Link
R. Chabra, J. E. Lenssen, E. Ilg, T. Schmidt, J. Straub, S. Lovegrove and R. Newcombe, "Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction" in European Conference on Computer Vision (ECCV), 2020.
 Link
M. Fey, J. Yuen and F. Weichert, "Hierarchical Inter-Message Passing for Learning on Molecular Graphs" in ICML Graph Representation Learning and Beyond (GRL+) (accepted for publication), 2020.
 PDF Link
Y. Zhao, T. Birdal, J. E. Lenssen, E. Menegatti, L. Guibas and F. Tombari, "Quaternion Equivariant Capsule Networks for 3D Point Clouds" in European Conference on Computer Vision (ECCV), 2020.
 Link
A. Böckenkamp, "roslaunch2: Versatile, Flexible and Dynamic Launch Configurations for the Robot Operating System" in Robot Operating System (ROS): The Complete Reference,Koubaa, Anis, Eds. Heidelberg: Springer International Publishing, 2020, pp. 165--181.
 Link

2019

M. Yayla, A. Toma, K. Chen, J. E. Lenssen, V. Shpacovitch, R. Hergenröder, F. Weichert and J. Chen, "Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms" , Sensors, Special Issue Surface Plasmon Resonance (SPR)-Based Sensors and Their Biological Applications, vol. 19, pp. 1-15, 2019.
 doi.org/10.3390/s19194138
C. Morris, M. Ritzert, M. Fey, W. L. Hamilton, J. E. Lenssen, G. Rattan and M. Grohe, "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks" in 33rd AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
 Datei
G. Rinkenauer, T. Plewan, D. Bachmann and F. Weichert, "Vergleich von virtuellen Interaktionssystemen mit einer realen Situation" , Arbeit interdisziplinär analysieren - bewerten - gestalten: 65. Kongress der Gesellschaft für Arbeitswissenschaft, vol. 6, pp. 1-6, 2019.
M. Yayla, A. Toma, J. E. Lenssen, J. Chen, F. Weichert and K. Chen, "Resource-efficient Nanoparticle Classification Using Frequency Domain Analysis" , Bildverarbeitung für die Medizin, pp. 339-344, 2019.
M. Fey, "Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
 Datei
A. Toma, J. Wenner, J. E. Lenssen and J. Chen, "Adaptive Quality Optimization of Computer Vision Tasks in Resource-Constrained Devices using Edge Computing" in 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019.
E. Rusakov, K. Brandenbusch, D. Fisseler, T. Somel, G. A. Fink, F. Weichert and G. Müller, "Generating Cuneiform Signs with Cycle-Consistent Adversarial Networks" , International Workshop on Historical Document Imaging and Processing (HIP19) , pp. 19-24, 2019.
M. Fey and J. E. Lenssen, "Fast Graph Representation Learning with PyTorch Geometric" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
 Datei
J. Deuse, L. Stankiewicz, R. Zwinkau and F. Weichert, "Automatic generation of methods-time measurement analyses for assembly tasks from motion capture data using convolutional neuronal networks - A proof of concept" , Advances in Human Factors and Systems Interaction (AHFE 2019), Advances in Intelligent Systems and Computing, vol. 959, pp. 141-150, 2019.
W. Tillmann, C. Schaak, J. Zajaczkowski, H. Müller, D. Hegels, M. Gaspar, B. Kuhlenkötter and D. D. Störkle, "Investigation of a procedure for the simulation-based optimisation of robot paths for thermal spraying" , Thermal Spray Bulletin, vol. 12, pp. 89-97, 2019.

2018

D. Bachmann, F. Bökler, J. Kopec, K. Popp, B. Schwarze and F. Weichert, "Multi-Objective Optimisation based Planning of Power-Line Grid Expansions" , ISPRS International Journal of Geo-Information, vol. 7, pp. 1-22, 2018.
 10.3390/ijgi7070258
J. E. Lenssen, M. Fey and P. Libuschewski, "Group Equivariant Capsule Networks" in Neural Information Processing Systems (NIPS) 32, 2018.
 Datei
D. Stoller, I. Vatolkin and H. Müller, "Intuitive and efficient computer aided music rearrangement with optimised processing of audio transitions" , Journal of New Music Research (accepted for publication), 2018.