Graph Neural Network
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Benchmarks
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Most implemented
SuperGlue: Learning Feature Matching with Graph Neural Networks
Hierarchical Graph Representation Learning with Differentiable Pooling
GNNExplainer: Generating Explanations for Graph Neural Networks
Inductive Relation Prediction by Subgraph Reasoning
Link Prediction Based on Graph Neural Networks
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Papers
Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes
Protein function annotation needs to know which predictions to distrust, not only what a model predicts. We ask whether tissue-specific interaction structure carries that information. Our candidate signal is effective re…
Graph Neural NetworkUnified Heterogeneous Graph Neural Network solver for Power Flow, Optimal Power Flow and State Estimation
Power Flow (PF), Optimal Power Flow (OPF), and State Estimation (SE) are fundamental problems in power system analysis, but solving them is computationally expensive. Graph Neural Networks (GNNs) have been proposed as fa…
Graph Neural NetworkFidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics. For current noisy devices, errors…
Graph Neural NetworkProMeta: Few-shot PROTAC-targeted degradation prediction across E3 ligases
Proteolysis-targeting chimeras (PROTACs) have emerged as a transformative therapeutic strategy that selectively degrades historically ''undruggable'' targets via the ubiquitin-proteasome system. Despite growing efforts t…
Graph Neural NetworkActivity PredictionMorphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion
Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed tomography (CBCT) is used for visual measurement, and the reconstructe…
Graph Neural NetworkPccDiffuser: Multi-solution Motion Planning for Continuum Robots
We present the PccDiffuser, a conditional diffusion framework for continuum robots that learns a multimodal distribution over complete configuration-space paths and samples multiple candidate solutions in parallel, which…
Computational EfficiencyGraph Neural NetworkMotion Planning