"expressive power" Papers
10 papers found
A Little Depth Goes a Long Way: The Expressive Power of Log-Depth Transformers
Will Merrill, Ashish Sabharwal
NeurIPS 2025posterarXiv:2503.03961
30
citations
Bridging Theory and Practice in Link Representation with Graph Neural Networks
Veronica Lachi, Francesco Ferrini, Antonio Longa et al.
NeurIPS 2025spotlightarXiv:2506.24018
1
citations
Aligning Transformers with Weisfeiler-Leman
Luis Müller, Christopher Morris
ICML 2024poster
Homomorphism Counts for Graph Neural Networks: All About That Basis
Emily Jin, Michael Bronstein, Ismail Ceylan et al.
ICML 2024poster
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Kangkang Lu, Yanhua Yu, Hao Fei et al.
AAAI 2024paperarXiv:2401.15603
On dimensionality of feature vectors in MPNNs
César Bravo, Alexander Kozachinskiy, Cristobal Rojas
ICML 2024poster
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
ICML 2024poster
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
ICML 2024poster
The Expressive Power of Path-Based Graph Neural Networks
Caterina Graziani, Tamara Drucks, Fabian Jogl et al.
ICML 2024poster
Weisfeiler-Leman at the margin: When more expressivity matters
Billy Franks, Christopher Morris, Ameya Velingker et al.
ICML 2024poster