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ORCIDChristopher Morris 0001
Person information
- affiliation: RWTH Aachen University, Germany
- affiliation (former): Mila - Quebec AI Institute, Canada
- affiliation (former): McGill University, Montreal, Quebec, Canada
- affiliation (former): Polytechnique Montréal, QC, Canada
- affiliation (former): TU Dortmund, Department of Computer Science, Germany
Other persons with the same name
- Christopher Morris 0002 — University of Birmingham, UK
- Christopher Morris 0003 — Carnegie Mellon University, Pittsburgh, PA, USA
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2020 – today
- 2024
[j6]Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek:
Attending to Graph Transformers. Trans. Mach. Learn. Res. 2024 (2024)- [c26]Chendi Qian, Didier Chételat, Christopher Morris:
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. AISTATS 2024: 1432-1440 - [c25]Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters:
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR 2024 - [c24]Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris:
Probabilistically Rewired Message-Passing Neural Networks. ICLR 2024 - [c23]Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Position: Future Directions in the Theory of Graph Machine Learning. ICML 2024 - [c22]Billy Joe Franks, Christopher Morris, Ameya Velingker, Floris Geerts:
Weisfeiler-Leman at the margin: When more expressivity matters. ICML 2024 - [c21]Luis Müller, Christopher Morris:
Aligning Transformers with Weisfeiler-Leman. ICML 2024 - [c20]Christopher Morris:
Towards a Theory of Machine Learning on Graphs and its Applications in Combinatorial Optimization. IJCAI 2024: 8553-8558 - [i33]Luis Müller, Christopher Morris:
Towards Principled Graph Transformers. CoRR abs/2401.10119 (2024) - [i32]Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Future Directions in Foundations of Graph Machine Learning. CoRR abs/2402.02287 (2024) - [i31]Billy Joe Franks, Christopher Morris, Ameya Velingker, Floris Geerts:
Weisfeiler-Leman at the margin: When more expressivity matters. CoRR abs/2402.07568 (2024) - [i30]Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert
:
Probabilistic Graph Rewiring via Virtual Nodes. CoRR abs/2405.17311 (2024) - [i29]Luis Müller, Christopher Morris:
Aligning Transformers with Weisfeiler-Leman. CoRR abs/2406.03148 (2024) - [i28]Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris:
Cometh: A continuous-time discrete-state graph diffusion model. CoRR abs/2406.06449 (2024) - 2023
- [j5]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial Optimization and Reasoning with Graph Neural Networks. J. Mach. Learn. Res. 24: 130:1-130:61 (2023) - [j4]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. J. Mach. Learn. Res. 24: 333:1-333:59 (2023) - [c19]Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe:
WL meet VC. ICML 2023: 25275-25302 - [c18]Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris:
Fine-grained Expressivity of Graph Neural Networks. NeurIPS 2023 - [i27]Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe:
WL meet VC. CoRR abs/2301.11039 (2023) - [i26]Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek:
Attending to Graph Transformers. CoRR abs/2302.04181 (2023) - [i25]Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris:
Fine-grained Expressivity of Graph Neural Networks. CoRR abs/2306.03698 (2023) - [i24]Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris:
Probabilistically Rewired Message-Passing Neural Networks. CoRR abs/2310.02156 (2023) - [i23]Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters:
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR abs/2310.04292 (2023) - [i22]Chendi Qian, Didier Chételat, Christopher Morris:
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. CoRR abs/2310.10603 (2023) - 2022
- [c17]Elias B. Khalil, Christopher Morris, Andrea Lodi:
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. AAAI 2022: 10219-10227 - [c16]Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh:
SpeqNets: Sparsity-aware permutation-equivariant graph networks. ICML 2022: 16017-16042 - [c15]Pablo Barceló, Mikhail Galkin, Christopher Morris, Miguel A. Romero Orth:
Weisfeiler and Leman Go Relational. LoG 2022: 46 - [c14]Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris:
Ordered Subgraph Aggregation Networks. NeurIPS 2022 - [p2]Nils M. Kriege, Christopher Morris:
The Weisfeiler-Leman Method for Machine Learning with Graphs. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 116-128 - [i21]Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR abs/2203.02433 (2022) - [i20]Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh:
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks. CoRR abs/2203.13913 (2022) - [i19]Elias B. Khalil, Christopher Morris, Andrea Lodi:
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. CoRR abs/2205.14210 (2022) - [i18]Chendi Qian, Gaurav Rattan, Floris Geerts, Christopher Morris, Mathias Niepert:
Ordered Subgraph Aggregation Networks. CoRR abs/2206.11168 (2022) - [i17]Pablo Barceló, Mikhail Galkin, Christopher Morris, Miguel A. Romero Orth:
Weisfeiler and Leman Go Relational. CoRR abs/2211.17113 (2022) - [i16]Martin Grohe, Stephan Günnemann, Stefanie Jegelka, Christopher Morris:
Graph Embeddings: Theory meets Practice (Dagstuhl Seminar 22132). Dagstuhl Reports 12(3): 141-155 (2022) - 2021
- [c13]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial Optimization and Reasoning with Graph Neural Networks. IJCAI 2021: 4348-4355 - [c12]Christopher Morris, Matthias Fey, Nils M. Kriege:
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. IJCAI 2021: 4543-4550 - [c11]Maxime Gasse, Simon Bowly, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao:
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) 2021: 220-231 - [c10]Leonardo Cotta, Christopher Morris, Bruno Ribeiro:
Reconstruction for Powerful Graph Representations. NeurIPS 2021: 1713-1726 - [i15]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial optimization and reasoning with graph neural networks. CoRR abs/2102.09544 (2021) - [i14]Christopher Morris, Matthias Fey, Nils M. Kriege:
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. CoRR abs/2105.05911 (2021) - [i13]Leonardo Cotta, Christopher Morris, Bruno Ribeiro:
Reconstruction for Powerful Graph Representations. CoRR abs/2110.00577 (2021) - [i12]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 abs/2112.09992 (2021) - 2020
- [j3]Nils M. Kriege, Fredrik D. Johansson, Christopher Morris:
A survey on graph kernels. Appl. Netw. Sci. 5(1): 6 (2020) - [j2]Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel:
Classifying Dissemination Processes in Temporal Graphs. Big Data 8(5): 363-378 (2020) - [c9]Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege:
Deep Graph Matching Consensus. ICLR 2020 - [c8]Christopher Morris, Gaurav Rattan, Petra Mutzel:
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings. NeurIPS 2020 - [c7]Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel:
Temporal Graph Kernels for Classifying Dissemination Processes. SDM 2020: 496-504 - [i11]Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege:
Deep Graph Matching Consensus. CoRR abs/2001.09621 (2020) - [i10]Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann:
TUDataset: A collection of benchmark datasets for learning with graphs. CoRR abs/2007.08663 (2020)
2010 – 2019
- 2019
- [b1]Christopher Morris:
Learning with graphs: kernel and neural approaches. Technical University of Dortmund, Germany, 2019 - [j1]Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel:
A unifying view of explicit and implicit feature maps of graph kernels. Data Min. Knowl. Discov. 33(6): 1505-1547 (2019) - [c6]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: 4602-4609 - [p1]Christopher Morris:
Lernen mit Graphen: Kern- und neuronale Methoden. Ausgezeichnete Informatikdissertationen 2019: 169-178 - [i9]Nils M. Kriege, Fredrik D. Johansson, Christopher Morris:
A Survey on Graph Kernels. CoRR abs/1903.11835 (2019) - [i8]Christopher Morris, Petra Mutzel:
Towards a practical k-dimensional Weisfeiler-Leman algorithm. CoRR abs/1904.01543 (2019) - [i7]Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel:
Temporal Graph Kernels for Classifying Dissemination Processes. CoRR abs/1911.05496 (2019) - 2018
- [c5]Nils M. Kriege, Christopher Morris, Anja Rey, Christian Sohler:
A Property Testing Framework for the Theoretical Expressivity of Graph Kernels. IJCAI 2018: 2348-2354 - [c4]Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec:
Hierarchical Graph Representation Learning with Differentiable Pooling. NeurIPS 2018: 4805-4815 - [i6]Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec:
Hierarchical Graph Representation Learning with Differentiable Pooling. CoRR abs/1806.08804 (2018) - [i5]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 abs/1810.02244 (2018) - 2017
- [c3]Christopher Morris, Kristian Kersting, Petra Mutzel:
Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs. ICDM 2017: 327-336 - [c2]Nils M. Kriege, Christopher Morris:
Recent Advances in Kernel-Based Graph Classification. ECML/PKDD (3) 2017: 388-392 - [i4]Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel:
A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels. CoRR abs/1703.00676 (2017) - [i3]Christopher Morris, Kristian Kersting, Petra Mutzel:
Global Weisfeiler-Lehman Graph Kernels. CoRR abs/1703.02379 (2017) - 2016
- [c1]Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel:
Faster Kernels for Graphs with Continuous Attributes via Hashing. ICDM 2016: 1095-1100 - [i2]Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel:
Faster Kernels for Graphs with Continuous Attributes via Hashing. CoRR abs/1610.00064 (2016) - [i1]Fritz Bökler, Matthias Ehrgott, Christopher Morris, Petra Mutzel:
Output-sensitive Complexity of Multiobjective Combinatorial Optimization. CoRR abs/1610.07204 (2016)
Coauthor Index
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