Conference Papers

• Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings (Preprint arXiv:1904:01543)
  Christopher Morris, Gaurav Rattan, Petra Mutzel,
  Neural Information Processing Systems (NeurIPS) 2020.

• Deep Graph Matching Consensus (Preprint arXiv:2001:09621)
  Matthias Fey, Jan E. Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege,
  International Conference on Learning Representations (ICLR) 2020.

• Temporal Graph Kernels for Classifying Dissemination Processes (Preprint arXiv:1911.05496)
  Lutz Oettershagen, Nils Kriege, Christopher Morris, Petra Mutzel,
  SIAM International Conference on Data Mining (SDM) 2020.

• Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks (Preprint arXiv:1810.02244)
  Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe,
  AAAI Conference on Artificial Intelligence (AAAI) 2019.
  Source Code Slides

• Hierarchical Graph Representation Learning with Differentiable Pooling (Preprint arXiv:1806.08804)
  Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec,
  Neural Information Processing Systems (NeurIPS) 2018, spotlight presentation, and KDD Deep Learning Day 2018.
  Source Code

• A Property Testing Framework for the Theoretical Expressivity of Graph Kernels
  Nils M. Kriege, Christopher Morris, Anja Rey, Christian Sohler,
  International Joint Conference on Artificial Intelligence (IJCAI) 2018.

• Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs (Preprint arXiv:1703.02379)
  Christopher Morris, Kristian Kersting, Petra Mutzel,
  IEEE International Conference on Data Mining (IEEE ICDM) 2017, full paper.
  Source Code Slides

• Recent Advances in Kernel-Based Graph Classification
  Nils M. Kriege, Christopher Morris,
  European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2017, nectar track.
  Slides

• Faster Kernels for Graphs with Continuous Attributes via Hashing (Preprint arXiv:1610.00064)
  Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel,
  IEEE International Conference on Data Mining (IEEE ICDM) 2016.
  Source Code

Journal Papers

• Output-sensitive Complexity of Multiobjective Combinatorial Optimization (Preprint arXiv:1610.07204)
  Fritz Bökler, Matthias Ehrgott, Christopher Morris, Petra Mutzel,
  Journal of Multicriteria Decision Analysis, 2016.

• A Survey on Graph Kernels (Preprint arXiv:1903.11835)
  Nils M. Kriege, Fredrik D. Johansson, Christopher Morris,
  Applied Network Science, Machine learning with graphs, 2020.

• A unifying view of explicit and implicit feature maps of graph kernels (Preprint arXiv:1703.00676)
  Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel,
  Data Mining and Knowledge Discovery, 2019.

• Classifying Dissemination Processes in Temporal Graphs
  Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel,
  Big Data, 2020.

Workshop Papers

• Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings (Preprint arXiv:1904.01543)
  Christopher Morris, Gaurav Rattan, Petra Mutzel,
  Graph Representation Learning and Beyond (GRL+, ICML 2020).

• TUDataset: A collection of benchmark datasets for learning with graphs (Preprint arXiv:2007.08663)
  Christopher Morris, Nils M. Kriege, Franka Bause Kristian Kersting, Petra Mutzel, Marion Neumann,
  Graph Representation Learning and Beyond (GRL+, ICML 2020).

Working Papers

• Combinatorial optimization and reasoning with graph neural networks (Preprint arXiv:2102.09544)
  Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic.
  

Thesis

• Learning with graphs: kernel and neural approaches
  Christopher Morris.