Matthias Fey

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 32

Top Topics

Graph Representation

Machine Learning

Replicator Dynamics

Top Venues

Eurographics (Short Papers)

Publications

Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec
RelBench: A Benchmark for Deep Learning on Relational Databases. CoRR (2024)
Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying
From Similarity to Superiority: Channel Clustering for Time Series Forecasting. CoRR (2024)
Keren Zhou, Karthik Ganapathi Subramanian, Po-Hsun Lin, Matthias Fey, Binqian Yin, Jiajia Li
FASTEN: Fast GPU-accelerated Segmented Matrix Multiplication for Heterogenous Graph Neural Networks. ICS (2024)
Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jure Leskovec, Matthias Fey
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning. CoRR (2024)
Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec
Relational Deep Learning: Graph Representation Learning on Relational Databases. CoRR (2023)
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR (2023)
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS (2023)
Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, Jure Leskovec
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs. NeurIPS Datasets and Benchmarks (2021)
Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, Jure Leskovec
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs. CoRR (2021)
Matthias Fey, Jan Eric Lenssen, Frank Weichert, Jure Leskovec
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings. ICML (2021)
Matthias Fey, Jan Eric Lenssen, Frank Weichert, Jure Leskovec
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings. CoRR (2021)
Christopher Morris, Matthias Fey, Nils M. Kriege
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. CoRR (2021)
Christopher Morris, Matthias Fey, Nils M. Kriege
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. IJCAI (2021)
Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
Weisfeiler and Leman go Machine Learning: The Story so far. CoRR (2021)
Matthias Fey, Jan-Gin Yuen, Frank Weichert
Hierarchical Inter-Message Passing for Learning on Molecular Graphs. CoRR (2020)
Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege
Deep Graph Matching Consensus. CoRR (2020)
Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege
Deep Graph Matching Consensus. ICLR (2020)
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec
Open Graph Benchmark: Datasets for Machine Learning on Graphs. NeurIPS (2020)
Marian Kleineberg, Matthias Fey, Frank Weichert
Adversarial Generation of Continuous Implicit Shape Representations. Eurographics (Short Papers) (2020)
Marian Kleineberg, Matthias Fey, Frank Weichert
Adversarial Generation of Continuous Implicit Shape Representations. CoRR (2020)
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec
Open Graph Benchmark: Datasets for Machine Learning on Graphs. CoRR (2020)
Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks. AAAI (2019)
Matthias Fey
Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks. CoRR (2019)
Matthias Fey, Jan Eric Lenssen
Fast Graph Representation Learning with PyTorch Geometric. CoRR (2019)
Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski
Group Equivariant Capsule Networks. NeurIPS (2018)
Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Müller
SplineCNN: Fast Geometric Deep Learning With Continuous B-Spline Kernels. CVPR (2018)
Nils M. Kriege, Matthias Fey, Denis Fisseler, Petra Mutzel, Frank Weichert
Recognizing Cuneiform Signs Using Graph Based Methods. COST@SDM (2018)
Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski
Group Equivariant Capsule Networks. CoRR (2018)
Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks. CoRR (2018)
Nils M. Kriege, Matthias Fey, Denis Fisseler, Petra Mutzel, Frank Weichert
Recognizing Cuneiform Signs Using Graph Based Methods. CoRR (2018)
Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Müller
SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels. CoRR (2017)
Christian Eichhorn, Matthias Fey, Gabriele Kern-Isberner
CP- and OCF-networks - a comparison. Fuzzy Sets Syst. 298 (2016)