GENIUS is an agentic AI framework that automates generation, validation, and repair of Quantum ESPRESSO DFT input files, succeeding on ~80% of 295 benchmarks with 76% autonomous repairs and lower cost than LLM-only baselines.
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Empirical comparison shows gradient-based explanations for GNN node similarities are actionable, consistent, and retain effects when sparsified, unlike mutual information explanations.
BioBLP is a modular embedding framework for multimodal biomedical KGs supporting heterogeneous attributes and missing data, with a pretraining strategy that improves results on drug-protein interaction prediction especially for low-degree entities.
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GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols
GENIUS is an agentic AI framework that automates generation, validation, and repair of Quantum ESPRESSO DFT input files, succeeding on ~80% of 295 benchmarks with 76% autonomous repairs and lower cost than LLM-only baselines.
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Explaining Graph Neural Networks for Node Similarity on Graphs
Empirical comparison shows gradient-based explanations for GNN node similarities are actionable, consistent, and retain effects when sparsified, unlike mutual information explanations.
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BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs
BioBLP is a modular embedding framework for multimodal biomedical KGs supporting heterogeneous attributes and missing data, with a pretraining strategy that improves results on drug-protein interaction prediction especially for low-degree entities.