Hierarchical graph representation learning with differentiable pooling R Ying, J You, C Morris, X Ren, WL Hamilton, J Leskovec Advances in Neural Information Processing Systems 32, 2018 | 1726 | 2018 |
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 (01), 4602-4609, 2019 | 1623 | 2019 |
TUDataset: A collection of benchmark datasets for learning with graphs C Morris, NM Kriege, F Bause, K Kersting, P Mutzel, M Neumann ICML 2020 Workshop on Graph Representation Learning and Beyond (GRL+ 2020), 2020 | 1010* | 2020 |
A survey on graph kernels NM Kriege, FD Johansson, C Morris Applied Network Science 5, 1-42, 2020 | 477 | 2020 |
Combinatorial Optimization and Reasoning with Graph Neural Networks PV Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi ... Journal of Machine Learning Research 24, 2023 | 341 | 2023 |
Deep graph matching consensus M Fey, JE Lenssen, C Morris, J Masci, NM Kriege ICLR 2020, 2020 | 230 | 2020 |
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings C Morris, G Rattan, P Mutzel Advances in Neural Information Processing Systems 33, 2020 | 174 | 2020 |
Faster kernels for graphs with continuous attributes via hashing C Morris, NM Kriege, K Kersting, P Mutzel 2016 IEEE 16th International Conference on Data Mining (ICDM), 1095-1100, 2016 | 124 | 2016 |
Weisfeiler and leman go machine learning: The story so far C Morris, Y Lipman, H Maron, B Rieck, NM Kriege, M Grohe, M Fey, ... Journal of Machine Learning Research 24, 2023 | 106 | 2023 |
Glocalized weisfeiler-lehman graph kernels: Global-local feature maps of graphs C Morris, K Kersting, P Mutzel 2017 IEEE International Conference on Data Mining (ICDM), 327-336, 2017 | 105 | 2017 |
Reconstruction for Powerful Graph Representations L Cotta, C Morris, B Ribeiro Advances in Neural Information Processing Systems 34, 2021 | 78 | 2021 |
Attending to graph transformers L Müller, M Galkin, C Morris, L Rampášek TMLR, 2024 | 67 | 2024 |
Ordered Subgraph Aggregation Networks C Qian, G Rattan, F Geerts, C Morris, M Niepert Advances in Neural Information Processing Systems 35, 2022 | 51 | 2022 |
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers EB Khalil, C Morris, A Lodi AAAI 2022, 2022 | 41 | 2022 |
A unifying view of explicit and implicit feature maps of graph kernels NM Kriege, M Neumann, C Morris, K Kersting, P Mutzel Data Mining and Knowledge Discovery 33, 1505-1547, 2019 | 37* | 2019 |
A Property Testing Framework for the Theoretical Expressivity of Graph Kernels NM Kriege, C Morris, A Rey, C Sohler IJCAI, 2348-2354, 2018 | 37 | 2018 |
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks C Morris, G Rattan, S Kiefer, S Ravanbakhsh ICML 2022, 2022 | 35 | 2022 |
Temporal graph kernels for classifying dissemination processes L Oettershagen, NM Kriege, C Morris, P Mutzel Proceedings of the 2020 SIAM International Conference on Data Mining, 496-504, 2020 | 35* | 2020 |
Output‐sensitive complexity of multiobjective combinatorial optimization F Bökler, M Ehrgott, C Morris, P Mutzel Journal of Multi‐Criteria Decision Analysis 24 (1-2), 25-36, 2017 | 28 | 2017 |
Weisfeiler and Leman Go Relational P Barcelo, M Galkin, C Morris, MR Orth Learning on Graphs Conference, 2022 | 27 | 2022 |