Jan Eric Lenssen

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Matthias FeyFounding Engineer @ kumo.aiVerified email at tu-dortmund.de
Christopher MorrisRWTH AachenVerified email at christophermorris.info
Martin GroheProfessor of Computer Science, RWTH Aachen UniversityVerified email at informatik.rwth-aachen.de
William L HamiltonAssistant Professor of Computer Science, McGill University and MilaVerified email at cs.mcgill.ca
Jonathan MasciNNAISENSE SAVerified email at nnaisense.com
Anas TomaDepartment of Computer Engineering, An-Najah National University, Nablus, Palestine.Verified email at najah.edu
Jian-Jia ChenProfessor of Computer Science, TU Dortmund University, GermanyVerified email at cs.uni-dortmund.de
Rohan ChabraUniversity of North Carolina at Chapel HillVerified email at cs.unc.edu
Julian StraubResearch Scientist, Reality Labs ResearchVerified email at csail.mit.edu
Tanner SchmidtFacebook Reality LabsVerified email at oculus.com
Richard NewcombeDirector of Research Science at Facebook Reality Labs, Surreal Vision Co-Founder, AffiliateVerified email at cs.washington.edu
Steven J LovegroveResearch Scientist at Facebook Reality LabsVerified email at fb.com
Eddy IlgProfessor at Saarland UniversityVerified email at cs.uni-saarland.de
Nils M. KriegeUniversity of ViennaVerified email at univie.ac.at
Tolga BirdalStanford UniversityVerified email at cs.stanford.edu
Federico TombariGoogle, TU MunichVerified email at in.tum.de
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Christian Osendorfer (Dr.)former TU MünchenVerified email at in.tum.de
Gerard Pons-MollProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
Keyang ZhouPhD Student, Max Planck Institute for InformaticsVerified email at mpi-inf.mpg.de

Jan Eric Lenssen

Max Planck Institute for Informatics

Verified email at mpi-inf.mpg.de

Differentiable algorithms Deep Learning GPU algorithms Computer vision Computer graphics


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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	1675	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	677	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	322	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	170	2020
Deep Graph Matching Consensus M Fey, JE Lenssen, C Morris, J Masci, NM Kriege International Conference on Learning Representation (ICLR 2020), 2020	124	2020
Group Equivariant Capsule Networks JE Lenssen, M Fey, P Libuschewski Advances in Neural Information Processing Systems (NeurIPS 2018), 8844-8853, 2018	100	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	59	2020
Gnnautoscale: Scalable and expressive graph neural networks via historical embeddings M Fey, JE Lenssen, F Weichert, J Leskovec International Conference on Machine Learning, 3294-3304, 2021	29	2021
Deep Iterative Surface Normal Estimation JE Lenssen, C Osendorfer, J Masci IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 2020	22*	2020
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	20	2017
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	11	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	8	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	7	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, 98-103, 2017	5	2017
Resource-Efficient Nanoparticle Classification Using Frequency Domain Analysis M Yayla, A Toma, JE Lenssen, V Shpacovitch, KH Chen, F Weichert, ... Bildverarbeitung für die Medizin 2019, 339-344, 2019	2	2019
Saving Energy for Cloud Applications in Mobile Devices Using Nearby Resources A Toma, A Starinow, JE Lenssen, JJ Chen 2018 26th Euromicro International Conference on Parallel, Distributed and …, 2018	2	2018
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	2	2017
TOCH: Spatio-Temporal Object Correspondence to Hand for Motion Refinement K Zhou, B Bhatnagar, JE Lenssen, G Pons-Moll European Conference on Computer Vision (ECCV 2022), 2022	1	2022
Differentiable Algorithms with Data-driven Parameterization in 3D Vision JE Lenssen Dissertation, 2022		2022
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		2022

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