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English(EN) What Comes Next and Why: Interpretable Next-Event Prediction with Neuro-Symbolic Rules

新的神经符号模型RULES增强了可解释的事件预测

研究人员开发了RULES,一种新颖的神经符号模型,专为可解释的下一事件预测而设计。该模型直接从数据中学习序列规则,解决了现有神经符号方法中的时间依赖性挑战。通过将RULES与残差网络结合形成RUNES(事件序列的规则网络),该系统在实现具有竞争力的准确性的同时,还提供了对影响预测的活跃规则的透明见解。 AI

影响 引入了一种新的可解释序列事件预测方法,有望提高AI系统的透明度。

排序理由 该集群包含一篇详细介绍新模型和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的神经符号模型RULES增强了可解释的事件预测

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该集群包含一篇详细介绍新模型和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Tim Nico Bauerschmidt, Isabel Valera, Jilles Vreeken ·

    What Comes Next and Why: Interpretable Next-Event Prediction with Neuro-Symbolic Rules

    arXiv:2610.31114v1 Announce Type: new Abstract: In real-world applications, being able to explain why a prediction is made is often as important - if not more so - than achieving high accuracy. However, existing methods for sequential event prediction typically prioritize accurac…