Jan Eric Lenssen
Cited by
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Fast Graph Representation Learning with PyTorch Geometric
M Fey, JE Lenssen
ICLR 2019 Workshop: Representation Learning on Graphs and Manifolds, 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
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
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
Deep Graph Matching Consensus
M Fey, JE Lenssen, C Morris, J Masci, NM Kriege
International Conference on Learning Representation (ICLR 2020), 2020
Group Equivariant Capsule Networks
JE Lenssen, M Fey, P Libuschewski
Advances in Neural Information Processing Systems (NeurIPS 2018), 8844-8853, 2018
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
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
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
Deep Iterative Surface Normal Estimation
JE Lenssen, C Osendorfer, J Masci
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 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
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
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
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
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
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
Real-time virus size classification using surface plasmon pamono resonance and convolutional neural networks
JE Lenssen, V Shpacovitch, F Weichert
Bildverarbeitung für die Medizin 2017: Algorithmen-Systeme-Anwendungen …, 2017
SimNP: Learning Self-Similarity Priors Between Neural Points
C Wewer, E Ilg, B Schiele, JE Lenssen
International Conference on Computer Vision (ICCV), 2023
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, ...
arXiv preprint arXiv:2312.04615, 2023
A Review of Nano-Particle Analysis with the PAMONO-Sensor
JE Lenssen, V Shpacovitch, D Siedhoff, P Libuschewski, R Hergenröder, ...
Biosens. Adv. Rev 1, 81-100, 2017
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