On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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3 results for “SGNNs”

Simulation as Supervision: Mechanistic Pretraining for Scientific Discoverycs.LG

SGNNs use simulations to train neural networks, improving scientific forecasting and interpretability.

problem Combining precise theory and machine learning for robust scientific modeling.

method Pretraining neural networks on diverse mechanistic simulations as training data.

result SGNNs outperform data-driven and physics-constrained models in forecasting and interpretability.

Simulation-Grounded Neural Networks SGNNs Scientific Forecasting Interpretability Machine Learning

2025-07-11abs ↗pdf ↗

Structured Multi-task Learning for Molecular Property Predictionq-bio.BM

Paper tackles multi-task learning for molecular property prediction with limited data.

problem Limited labeled data for each molecular property task in drug discovery.

method Proposes SGNN-EBM method to utilize relation graph between tasks and improve multi-task learning performance.

result Empirical results show the effectiveness of SGNN-EBM.

multi-task learning molecular property prediction drug discovery limited data structured task modeling

2022-02-22abs ↗pdf ↗

On the Universality of Graph Neural Networks on Large Random Graphsstat.ML

Graph Neural Networks struggle on random graphs without node identifiers.

problem Graph Neural Networks' limitations on random graphs without node identifiers.

method Study of Graph Neural Networks and Structural Graph Neural Networks convergence on large random graphs.

result Structural Graph Neural Networks are more powerful and universal than Graph Neural Networks on random graphs.

Graph Neural Networks Random Graphs Structural Graph Neural Networks Universality Stochastic Block Model

2021-05-27abs ↗pdf ↗