Παρακολούθηση
Matthias Fey
Matthias Fey
Founding Engineer @ kumo.ai
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα tu-dortmund.de - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Fast graph representation learning with PyTorch Geometric
M Fey, JE Lenssen
arXiv preprint arXiv:1903.02428, 2019
52472019
Open graph benchmark: Datasets for machine learning on graphs
W Hu, M Fey, M Zitnik, Y Dong, H Ren, B Liu, M Catasta, J Leskovec
Advances in neural information processing systems 33, 22118-22133, 2020
30792020
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
19642019
Splinecnn: Fast geometric deep learning with continuous b-spline kernels
M Fey, JE Lenssen, F Weichert, H Müller
Proceedings of the IEEE conference on computer vision and pattern …, 2018
5742018
Ogb-lsc: A large-scale challenge for machine learning on graphs
W Hu, M Fey, H Ren, M Nakata, Y Dong, J Leskovec
arXiv preprint arXiv:2103.09430, 2021
4572021
Deep graph matching consensus
M Fey, JE Lenssen, C Morris, J Masci, NM Kriege
arXiv preprint arXiv:2001.09621, 2020
2532020
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
1842021
Group equivariant capsule networks
JE Lenssen, M Fey, P Libuschewski
Advances in neural information processing systems 31, 2018
1542018
Weisfeiler and leman go machine learning: The story so far
C Morris, Y Lipman, H Maron, B Rieck, NM Kriege, M Grohe, M Fey, ...
The Journal of Machine Learning Research 24 (1), 15865-15923, 2023
1362023
Fast graph representation learning with pytorch geometric, 2019
M Fey, JE Lenssen
arXiv preprint arXiv:1903.02428, 1903
1201903
Temporal graph benchmark for machine learning on temporal graphs
S Huang, F Poursafaei, J Danovitch, M Fey, W Hu, E Rossi, J Leskovec, ...
Advances in Neural Information Processing Systems 36, 2024
942024
Hierarchical inter-message passing for learning on molecular graphs
M Fey, JG Yuen, F Weichert
arXiv preprint arXiv:2006.12179, 2020
922020
Adversarial generation of continuous implicit shape representations
M Kleineberg, M Fey, F Weichert
arXiv preprint arXiv:2002.00349, 2020
742020
Just jump: Dynamic neighborhood aggregation in graph neural networks
M Fey
arXiv preprint arXiv:1904.04849, 2019
582019
Recognizing cuneiform signs using graph based methods
NM Kriege, M Fey, D Fisseler, P Mutzel, F Weichert
International Workshop on Cost-Sensitive Learning, 31-44, 2018
392018
The power of the Weisfeiler-Leman algorithm for machine learning with graphs
C Morris, M Fey, NM Kriege
arXiv preprint arXiv:2105.05911, 2021
312021
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
18*2023
Pytorch frame: A modular framework for multi-modal tabular learning
W Hu, Y Yuan, Z Zhang, A Nitta, K Cao, V Kocijan, J Sunil, J Leskovec, ...
arXiv preprint arXiv:2404.00776, 2024
122024
CP-and OCF-networks–a comparison
C Eichhorn, M Fey, G Kern-Isberner
Fuzzy sets and Systems 298, 109-127, 2016
112016
Relbench: A benchmark for deep learning on relational databases
J Robinson, R Ranjan, W Hu, K Huang, J Han, A Dobles, M Fey, ...
arXiv preprint arXiv:2407.20060, 2024
62024
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