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TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Neural Information Processing Systems
Temporal graphs are widely used to model dynamic systems with time-varying interactions.
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Byzantine-Tolerant Methods for Distributed Variational Inequalities
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Robustness to Byzantine attacks is a necessity for various distributed training scenarios.
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IND 2W
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LM significantly improves the effectiveness and efficiency of LLMs.
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UC Santa Barbara develops new soft robotic system for emergency intubation procedures
A new soft robotic device from UC Santa Barbara makes emergency intubation easier, allowing non-experts to place breathing tubes in just 21 seconds on average.
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