English(EN) SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data

新的SSH-Net模型使用深度学习预测GPU故障时间

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-18 16:29

研究人员开发了SSH-Net，这是一种新颖的深度神经网络，旨在预测具有竞争风险的系统（如GPU）的失效时间分布。这种结构化分段风险深度神经网络将网络结构与数据结构相关联，允许不同的数据组通过单独的子网络影响预测。该模型输出特定原因的风险函数，并通过模拟进行了验证，并应用于Titan GPU的失效时间数据。 AI

影响该模型可以改进对GPU等复杂工程系统的可靠性和维护预测。

排序理由该集群描述了一篇关于新型深度神经网络模型的新学术论文。

在 arXiv stat.ML 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv stat.ML TIER_1 English(EN) · Jie Min, Yueyao Wang, Mengkun Chen · 2026-06-19 04:00

SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data

arXiv:2606.20451v1 Announce Type: new Abstract: Competing risks are commonly observed in engineering fields and can bring challenges to time-to-event data modeling when the application scenarios are complicated. Recently, deep neural networks have received great attention for pre…
arXiv stat.ML TIER_1 English(EN) · Mengkun Chen · 2026-06-18 16:29

SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data

Competing risks are commonly observed in engineering fields and can bring challenges to time-to-event data modeling when the application scenarios are complicated. Recently, deep neural networks have received great attention for prediction with competing risks, due to their flexi…

报道来源 [2]

SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data

SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data

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