NeurPRISE trains a GNN-Transformer via imitation learning to mimic a lookahead heuristic for scenario reduction in 2RO, delivering 7-200x speedups with competitive regret on three test problems and zero-shot generalization.
Strategies for pre-training graph neural networks
4 Pith papers cite this work. Polarity classification is still indexing.
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CHCL aligns a Cheeger-Hodge joint signature across graph augmentations to produce embeddings that remain stable under local structural changes.
Topology-aware large graph representations of polymer chains combined with masked pretraining on unlabeled data reduce prediction error for glass transition temperature by 5.1% compared to repeat-unit baselines.
A systematic survey and benchmark of four deep learning paradigms for molecular property prediction that organizes the field, critiques current data practices, and outlines three future directions.
citing papers explorer
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Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
NeurPRISE trains a GNN-Transformer via imitation learning to mimic a lookahead heuristic for scenario reduction in 2RO, delivering 7-200x speedups with competitive regret on three test problems and zero-shot generalization.
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Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning
CHCL aligns a Cheeger-Hodge joint signature across graph augmentations to produce embeddings that remain stable under local structural changes.
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It's All Connected: Topology-Aware Structural Graph Encoding Improves Performance on Polymer Prediction
Topology-aware large graph representations of polymer chains combined with masked pretraining on unlabeled data reduce prediction error for glass transition temperature by 5.1% compared to repeat-unit baselines.
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A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era
A systematic survey and benchmark of four deep learning paradigms for molecular property prediction that organizes the field, critiques current data practices, and outlines three future directions.