Christopher Morris

86 papers A* 24A 2Journal 53Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GraIP: A Benchmarking Framework For Neural Graph Inverse Problems. CoRR Semih Cantürk, Andrei Manolache, Arman Mielke, Chendi Qian, Antoine Siraudin, Christopher Morris, Mathias Niepert, Guy Wolf
2026	J	`jnl`	Learning to Approximate Uniform Facility Location via Graph Neural Networks. CoRR Chendi Qian, Christopher Morris, Stefanie Jegelka, Christian Sohler
2026	J	`jnl`	Position: Message-passing and spectral GNNs are two sides of the same coin. CoRR Antonis Vasileiou, Juan Cerviño, Pascal Frossard, Charilaos I. Kanatsoulis, Christopher Morris, Michael T. Schaub, Pierre Vandergheynst, Zhiyang Wang, Guy Wolf, Ron Levie
2026	J	`jnl`	Principled Latent Diffusion for Graphs via Laplacian Autoencoders. CoRR Antoine Siraudin, Christopher Morris
2026	J	`jnl`	Which Algorithms Can Graph Neural Networks Learn? CoRR Solveig Wittig, Antonis Vasileiou, Robert R. Nerem, Timo Stoll, Floris Geerts, Yusu Wang, Christopher Morris
2025	J	`jnl`	Cometh: A continuous-time discrete-state graph diffusion model. Trans. Mach. Learn. Res. Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris
2025	A*	`conf`	Covered Forest: Fine-grained generalization analysis of graph neural networks. ICML Antonis Vasileiou, Ben Finkelshtein, Floris Geerts, Ron Levie, Christopher Morris
2025	J	`jnl`	Generalizable Insights for Graph Transformers in Theory and Practice. CoRR Timo Stoll, Luis Müller, Christopher Morris
2025	J	`jnl`	GraphBench: Next-generation graph learning benchmarking. CoRR Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael M. Bronstein, Mikhail Galkin, Holger H. Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris
2025	—	`conf`	Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks. ICML (Position Papers) Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025	J	`jnl`	Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks. CoRR Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025	J	`jnl`	Principled data augmentation for learning to solve quadratic programming problems. CoRR Chendi Qian, Christopher Morris
2025	J	`jnl`	Survey on Generalization Theory for Graph Neural Networks. CoRR Antonis Vasileiou, Stefanie Jegelka, Ron Levie, Christopher Morris
2025	J	`jnl`	Towards graph neural networks for provably solving convex optimization problems. CoRR Chendi Qian, Christopher Morris
2025	J	`jnl`	Understanding Generalization in Node and Link Prediction. CoRR Antonis Vasileiou, Timo Stoll, Christopher Morris
2024	A*	`conf`	Aligning Transformers with Weisfeiler-Leman. ICML Luis Müller, Christopher Morris
2024	J	`jnl`	Aligning Transformers with Weisfeiler-Leman. CoRR Luis Müller, Christopher Morris
2024	J	`jnl`	Attending to Graph Transformers. Trans. Mach. Learn. Res. Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek
2024	J	`jnl`	Cometh: A continuous-time discrete-state graph diffusion model. CoRR Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris
2024	J	`jnl`	Covered Forest: Fine-grained generalization analysis of graph neural networks. CoRR Antonis Vasileiou, Ben Finkelshtein, Floris Geerts, Ron Levie, Christopher Morris
2024	A	`conf`	Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. AISTATS Chendi Qian, Didier Chételat, Christopher Morris
2024	J	`jnl`	Future Directions in Foundations of Graph Machine Learning. CoRR Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024	A*	`conf`	Position: Future Directions in the Theory of Graph Machine Learning. ICML Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024	A*	`conf`	Probabilistic Graph Rewiring via Virtual Nodes. NeurIPS Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert
2024	J	`jnl`	Probabilistic Graph Rewiring via Virtual Nodes. CoRR Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert
2024	A*	`conf`	Probabilistically Rewired Message-Passing Neural Networks. ICLR Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris
2024	A*	`conf`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR 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
2024	A*	`conf`	Towards Principled Graph Transformers. NeurIPS Luis Müller, Daniel Kusuma, Blai Bonet, Christopher Morris
2024	J	`jnl`	Towards Principled Graph Transformers. CoRR Luis Müller, Christopher Morris
2024	A*	`conf`	Towards a Theory of Machine Learning on Graphs and its Applications in Combinatorial Optimization. IJCAI Christopher Morris
2024	A*	`conf`	Weisfeiler-Leman at the margin: When more expressivity matters. ICML Billy Joe Franks, Christopher Morris, Ameya Velingker, Floris Geerts
2024	J	`jnl`	Weisfeiler-Leman at the margin: When more expressivity matters. CoRR Billy Joe Franks, Christopher Morris, Ameya Velingker, Floris Geerts
2023	J	`jnl`	Attending to Graph Transformers. CoRR Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek
2023	J	`jnl`	Combinatorial Optimization and Reasoning with Graph Neural Networks. J. Mach. Learn. Res. Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2023	J	`jnl`	Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. CoRR Chendi Qian, Didier Chételat, Christopher Morris
2023	A*	`conf`	Fine-grained Expressivity of Graph Neural Networks. NeurIPS Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
2023	J	`jnl`	Fine-grained Expressivity of Graph Neural Networks. CoRR Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
2023	J	`jnl`	Probabilistically Rewired Message-Passing Neural Networks. CoRR Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris
2023	J	`jnl`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR 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
2023	A*	`conf`	WL meet VC. ICML Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe
2023	J	`jnl`	WL meet VC. CoRR Christopher Morris, Floris Geerts, Jan Tönshoff, Martin Grohe
2023	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. J. Mach. Learn. Res. Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2022	J	`jnl`	Graph Embeddings: Theory meets Practice (Dagstuhl Seminar 22132). Dagstuhl Reports Martin Grohe, Stephan Günnemann, Stefanie Jegelka, Christopher Morris
2022	A*	`conf`	MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. AAAI Elias B. Khalil, Christopher Morris, Andrea Lodi
2022	J	`jnl`	MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers. CoRR Elias B. Khalil, Christopher Morris, Andrea Lodi
2022	A*	`conf`	Ordered Subgraph Aggregation Networks. NeurIPS Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris
2022	J	`jnl`	Ordered Subgraph Aggregation Networks. CoRR Chendi Qian, Gaurav Rattan, Floris Geerts, Christopher Morris, Mathias Niepert
2022	J	`jnl`	SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks. CoRR Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh
2022	A*	`conf`	SpeqNets: Sparsity-aware permutation-equivariant graph networks. ICML Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh
2022	J	`jnl`	The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR 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
2022	—	`ch.`	The Weisfeiler-Leman Method for Machine Learning with Graphs. Mach. Learn. under Resour. Constraints Vol. 1 (1) Nils M. Kriege, Christopher Morris
2022	—	`conf`	Weisfeiler and Leman Go Relational. LoG Pablo Barceló, Mikhail Galkin, Christopher Morris, Miguel A. Romero Orth
2022	J	`jnl`	Weisfeiler and Leman Go Relational. CoRR Pablo Barceló, Mikhail Galkin, Christopher Morris, Miguel A. Romero Orth
2021	A*	`conf`	Combinatorial Optimization and Reasoning with Graph Neural Networks. IJCAI Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2021	J	`jnl`	Combinatorial optimization and reasoning with graph neural networks. CoRR Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2021	A*	`conf`	Reconstruction for Powerful Graph Representations. NeurIPS Leonardo Cotta, Christopher Morris, Bruno Ribeiro
2021	J	`jnl`	Reconstruction for Powerful Graph Representations. CoRR Leonardo Cotta, Christopher Morris, Bruno Ribeiro
2021	—	`conf`	The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) 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
2021	A*	`conf`	The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. IJCAI Christopher Morris, Matthias Fey, Nils M. Kriege
2021	J	`jnl`	The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs. CoRR Christopher Morris, Matthias Fey, Nils M. Kriege
2021	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. CoRR Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2020	J	`jnl`	A survey on graph kernels. Appl. Netw. Sci. Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2020	J	`jnl`	Classifying Dissemination Processes in Temporal Graphs. Big Data Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel
2020	A*	`conf`	Deep Graph Matching Consensus. ICLR Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege
2020	J	`jnl`	Deep Graph Matching Consensus. CoRR Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege
2020	J	`jnl`	TUDataset: A collection of benchmark datasets for learning with graphs. CoRR Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann
2020	A	`conf`	Temporal Graph Kernels for Classifying Dissemination Processes. SDM Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel
2020	A*	`conf`	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings. NeurIPS Christopher Morris, Gaurav Rattan, Petra Mutzel
2019	J	`jnl`	A Survey on Graph Kernels. CoRR Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2019	J	`jnl`	A unifying view of explicit and implicit feature maps of graph kernels. Data Min. Knowl. Discov. Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel
2019	—	`—`	Learning with graphs: kernel and neural approaches. Christopher Morris
2019	—	`ch.`	Lernen mit Graphen: Kern- und neuronale Methoden. Ausgezeichnete Informatikdissertationen Christopher Morris
2019	J	`jnl`	Temporal Graph Kernels for Classifying Dissemination Processes. CoRR Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel
2019	J	`jnl`	Towards a practical k-dimensional Weisfeiler-Leman algorithm. CoRR Christopher Morris, Petra Mutzel
2019	A*	`conf`	Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks. AAAI Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
2018	A*	`conf`	A Property Testing Framework for the Theoretical Expressivity of Graph Kernels. IJCAI Nils M. Kriege, Christopher Morris, Anja Rey, Christian Sohler
2018	A*	`conf`	Hierarchical Graph Representation Learning with Differentiable Pooling. NeurIPS Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec
2018	J	`jnl`	Hierarchical Graph Representation Learning with Differentiable Pooling. CoRR Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec
2018	J	`jnl`	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks. CoRR Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
2017	J	`jnl`	A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels. CoRR Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel
2017	J	`jnl`	Global Weisfeiler-Lehman Graph Kernels. CoRR Christopher Morris, Kristian Kersting, Petra Mutzel
2017	A*	`conf`	Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs. ICDM Christopher Morris, Kristian Kersting, Petra Mutzel
2017	—	`conf`	Recent Advances in Kernel-Based Graph Classification. ECML/PKDD (3) Nils M. Kriege, Christopher Morris
2016	A*	`conf`	Faster Kernels for Graphs with Continuous Attributes via Hashing. ICDM Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel
2016	J	`jnl`	Faster Kernels for Graphs with Continuous Attributes via Hashing. CoRR Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel
2016	J	`jnl`	Output-sensitive Complexity of Multiobjective Combinatorial Optimization. CoRR Fritz Bökler, Matthias Ehrgott, Christopher Morris, Petra Mutzel