| Fast Graph Representation Learning with PyTorch Geometric M Fey, JE Lenssen ICLR 2019 Workshop: Representation Learning on Graphs and Manifolds, 2019 | 5221 | 2019 |
| Weisfeiler and leman go neural: Higher-order graph neural networks C Morris, M Ritzert, M Fey, WL Hamilton, JE Lenssen, G Rattan, M Grohe Proceedings of the AAAI Conference on Artificial Intelligence 33, 4602-4609, 2019 | 1949 | 2019 |
| SplineCNN: Fast geometric deep learning with continuous B-spline kernels M Fey, JE Lenssen, F Weichert, H Müller IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), 869-877, 2018 | 575 | 2018 |
| Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction R Chabra, JE Lenssen, E Ilg, T Schmidt, J Straub, S Lovegrove, ... European Conference on Computer Vision (ECCV 2020), 2020 | 498 | 2020 |
| Deep Graph Matching Consensus M Fey, JE Lenssen, C Morris, J Masci, NM Kriege International Conference on Learning Representation (ICLR 2020), 2020 | 252 | 2020 |
| Gnnautoscale: Scalable and expressive graph neural networks via historical embeddings M Fey, JE Lenssen, F Weichert, J Leskovec International Conference on Machine Learning (ICML 2021), 3294-3304, 2021 | 183 | 2021 |
| Group Equivariant Capsule Networks JE Lenssen, M Fey, P Libuschewski Advances in Neural Information Processing Systems (NeurIPS 2018), 8844-8853, 2018 | 154 | 2018 |
| Quaternion Equivariant Capsule Networks for 3D Point Clouds Y Zhao, T Birdal, JE Lenssen, E Menegatti, L Guibas, F Tombari European Conference on Computer Vision (ECCV 2020), 2020 | 108 | 2020 |
| Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields G Tiwari, D Antic, JE Lenssen, N Sarafianos, T Tung, G Pons-Moll European Conference on Computer Vision (ECCV 2022), 2022 | 99 | 2022 |
| Deep Iterative Surface Normal Estimation JE Lenssen, C Osendorfer, J Masci IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 2020 | 71 | 2020 |
| TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinement K Zhou, B Bhatnagar, JE Lenssen, G Pons-Moll European Conference on Computer Vision (ECCV 2022), 2022 | 51 | 2022 |
| latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction C Wewer, K Raj, E Ilg, B Schiele, JE Lenssen European Conference on Computer Vision (ECCV 2024), 2024 | 41 | 2024 |
| Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction D Das, C Wewer, R Yunus, E Ilg, JE Lenssen IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024), 2023 | 36 | 2023 |
| Application of the PAMONO-sensor for quantification of microvesicles and determination of nano-particle size distribution V Shpacovitch, I Sidorenko, JE Lenssen, V Temchura, F Weichert, ... Sensors 17 (2), 244, 2017 | 31 | 2017 |
| Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes R Yunus, JE Lenssen, M Niemeyer, Y Liao, C Rupprecht, C Theobalt, ... Computer Graphics Forum, e15062, 2024 | 18 | 2024 |
| Relational Deep Learning: Graph Representation Learning on Relational Databases M Fey, W Hu, K Huang, JE Lenssen, R Ranjan, J Robinson, R Ying, J You, ... ICML 2024 Position Papers, 2023 | 18* | 2023 |
| Real-time Low SNR Signal Processing for Nanoparticle Analysis with Deep Neural Networks. JE Lenssen, A Toma, A Seebold, V Shpacovitch, P Libuschewski, ... BIOSIGNALS, 36-47, 2018 | 14 | 2018 |
| Adaptive Quality Optimization of Computer Vision Tasks in Resource-Constrained Devices using Edge Computing A Toma, J Wenner, JE Lenssen, JJ Chen 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2019 | 12 | 2019 |
| Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms M Yayla, A Toma, KH Chen, JE Lenssen, V Shpacovitch, R Hergenröder, ... Sensors 19 (19), 4138, 2019 | 12 | 2019 |
| Improving 2D Feature Representations by 3D-Aware Fine-Tuning Y Yue, A Das, F Engelmann, S Tang, JE Lenssen European Conference on Computer Vision (ECCV 2024), 2024 | 11 | 2024 |
Matthias FeyFounding Engineer @ kumo.ai確認したメール アドレス: tu-dortmund.de