ROAM routes region tokens to MoE experts via entropic optimal transport with per-slide capacity marginals and graph regularization, achieving competitive performance and external AUC 0.845 on NSCLC WSI benchmarks.
Advances in neural information processing systems30(2017)
3 Pith papers cite this work. Polarity classification is still indexing.
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A GNN-based hybrid twin learns the ignorance component of physics simulations from sparse data and generalizes corrections across meshes, geometries, and loads in nonlinear heat transfer.
Graph neural networks outperform non-graph baselines like MLP in F1 score on seven multilingual misinformation datasets while maintaining similar or better inference efficiency.
citing papers explorer
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Region-Graph Optimal Transport Routing for Mixture-of-Experts Whole-Slide Image Classification
ROAM routes region tokens to MoE experts via entropic optimal transport with per-slide capacity marginals and graph regularization, achieving competitive performance and external AUC 0.845 on NSCLC WSI benchmarks.
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Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework
A GNN-based hybrid twin learns the ignorance component of physics simulations from sparse data and generalizes corrections across meshes, geometries, and loads in nonlinear heat transfer.
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Graph Neural Networks for Misinformation Detection: Performance-Efficiency Trade-offs
Graph neural networks outperform non-graph baselines like MLP in F1 score on seven multilingual misinformation datasets while maintaining similar or better inference efficiency.