expressive power

Aggregate-Combine-Readout GNNs Can Express Logical Classifiers Beyond the Logic C2 AAAI 2026 Expressive Power of Graph Transformers via Logic AAAI 2026 Logical Characterizations of GNNs with Mean Aggregation AAAI 2026 Circuit Complexity Bounds for RoPE-based Transformer Architecture EMNLP 2025 Expressive Power of Temporal Message Passing AAAI 2025 How Expressive are Knowledge Graph Foundation Models? ICML 2025 Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman Algorithms ICML 2025 KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks ICLR 2025 Looped ReLU MLPs May Be All You Need as Practical Programmable Computers AISTATS 2025 On the Expressive Power of Sparse Geometric MPNNs ICLR 2025 Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power JMLR 2025 Pruning for GNNs: Lower Complexity with Comparable Expressiveness ICML 2025 The impact of allocation strategies in subset learning on the expressive power of neural networks ICLR 2025 Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming ICLR 2025 Aligning Transformers with Weisfeiler-Leman ICML 2024 Almost Surely Asymptotically Constant Graph Neural Networks NeurIPS 2024 Deep Homomorphism Networks NeurIPS 2024 Deep Network Approximation: Beyond ReLU to Diverse Activation Functions JMLR 2024 Homomorphism Counts for Graph Neural Networks: All About That Basis ICML 2024 How Smooth Is Attention? ICML 2024 Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction AAAI 2024 Logical characterizations of recurrent graph neural networks with reals and floats NeurIPS 2024 On the Expressive Power of Spectral Invariant Graph Neural Networks ICML 2024 On the Expressive Power of Tree-Structured Probabilistic Circuits NeurIPS 2024 On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning ICLR 2024