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English(EN) Deep4ge: DNN Training Trajectories for Fault Detection and Diagnosis

Deep4ge 数据集发布，用于 DNN 故障检测和诊断 · 跟踪 2 个来源

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出了 Deep4ge，这是一个新的基准数据集，旨在帮助检测和诊断深度学习系统中的故障。该数据集包含来自 Stack Overflow 的 59 个改编的 TensorFlow/Keras 程序生成的 14,000 多个训练运行。这些运行包括通过 27 种源代码转换创建的近 10,000 个故障变体，以及 4,000 多个正确的基线运行。Deep4ge 捕获每个 epoch 的 26 个特征，例如权重、梯度和准确性趋势，以支持二元故障检测、多类诊断和早期预测等任务。 AI

影响 提供了一个标准化的数据集，用于提高深度学习模型的可靠性和鲁棒性。

排序理由 该集群描述了一个用于研究目的的新数据集和框架，已在 arXiv 上发布。

在 arXiv cs.LG 阅读 →

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

Deep4ge 数据集发布，用于 DNN 故障检测和诊断 · 跟踪 2 个来源

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该集群描述了一个用于研究目的的新数据集和框架，已在 arXiv 上发布。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Sigma Jahan ·

    Deep4ge：用于故障检测和诊断的DNN训练轨迹

    arXiv:2607.12868v1 Announce Type: cross Abstract: Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect and diagnose such failures from changes observed across training epochs. However, the softwar…

  2. arXiv cs.LG TIER_1 English(EN) · Sigma Jahan ·

    Deep4ge：用于故障检测和诊断的 DNN 训练轨迹

    Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect and diagnose such failures from changes observed across training epochs. However, the software engineering community still lacks a public datas…

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