← Authors

Christopher Morris

26 papers · 2018–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (17) 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (13) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (7) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (34) πŸ”¬ Deep Specialist (17) 🧬 Topic Evolution πŸ† Keyword Champion (5) ⚑ Prolific Year (9) πŸ’Ž Century Club (26) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (54) πŸš€ Conference Pioneer

Conferences

ICML (7) NIPS (7) IJCAI (4) ICLR (3) AAAI (2) JMLR (2) AISTATS (1)

Top co-authors

Gaurav Rattan (4) Luis MΓΌller (4) Matthias Fey (4) Floris Geerts (4) Chendi Qian (4) Martin Grohe (4) Mathias Niepert (4) Andrea Lodi (3) Didier Chetelat (3) Elias B. Khalil (3)

Keywords

graph neural network (17) graph isomorphism (5) message passing (5) combinatorial optimization (5) graph classification (5) expressive power (3) weisfeiler-lehman algorithm (3) node classification (3) weisfeiler-leman algorithm (3) representation learning (2) graph kernel (2) permutation equivariance (2) mixed-integer programming (2) relational datum (2) weisfeiler-lemann algorithm (2) linear programming (1) hierarchical representation (1) vc dimension (1) warm starting (1) generalization bound (1)

Papers

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks ICML 2025
Covered Forest: Fine-grained generalization analysis of graph neural networks ICML 2025
Aligning Transformers with Weisfeiler-Leman ICML 2024
Probabilistic Graph Rewiring via Virtual Nodes NIPS 2024
Towards Principled Graph Transformers NIPS 2024
Towards a Theory of Machine Learning on Graphs and its Applications in Combinatorial Optimization IJCAI 2024
Weisfeiler-Leman at the margin: When more expressivity matters ICML 2024
Position: Future Directions in the Theory of Graph Machine Learning ICML 2024
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems AISTATS 2024
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets ICLR 2024
Probabilistically Rewired Message-Passing Neural Networks ICLR 2024
Weisfeiler and Leman go Machine Learning: The Story so far JMLR 2023
Combinatorial Optimization and Reasoning with Graph Neural Networks JMLR 2023
WL meet VC ICML 2023
Fine-grained Expressivity of Graph Neural Networks NIPS 2023
SpeqNets: Sparsity-aware permutation-equivariant graph networks ICML 2022
Ordered Subgraph Aggregation Networks NIPS 2022
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers AAAI 2022
Combinatorial Optimization and Reasoning with Graph Neural Networks IJCAI 2021
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs IJCAI 2021
Reconstruction for Powerful Graph Representations NIPS 2021
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings NIPS 2020
Deep Graph Matching Consensus ICLR 2020
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks AAAI 2019
A Property Testing Framework for the Theoretical Expressivity of Graph Kernels IJCAI 2018
Hierarchical Graph Representation Learning with Differentiable Pooling NIPS 2018