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English(EN) TorchDCM: A Unified PyTorch-Native Package for Discrete Choice Modeling

TorchDCM 包提供更快的 PyTorch 离散选择建模

研究人员开发了 TorchDCM,一个新推出的开源 Python 包,旨在利用 PyTorch 简化离散选择建模 (DCM)。该包旨在弥合传统计量经济学工作流程与可扩展、可微分计算之间的差距,特别是对于大型和计算密集型模型。TorchDCM 提供了全面的计量经济学功能,支持各种似然函数和模型规范,并显示出比现有软件显著的速度提升,尤其是在使用 CUDA 设备时。 AI

影响 通过提供更快、更具可扩展性的计算框架,加速计量经济学建模的研究和开发。

排序理由 该集群描述了一个新的开源离散选择建模包,该包已作为 arXiv 论文发布。[lever_c_demoted from research: ic=1 ai=0.7]

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 →

TorchDCM 包提供更快的 PyTorch 离散选择建模

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该集群描述了一个新的开源离散选择建模包,该包已作为 arXiv 论文发布。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Baichuan Mo, Zhengzhong Ricky You, Xiqun Michael Chen, Ruimin Li ·

    TorchDCM:一个统一的 PyTorch 原生离散选择建模包

    arXiv:2608.19231v1 Announce Type: cross Abstract: Estimating large and simulation-intensive discrete choice models (DCMs) requires repeated evaluation of utilities, probabilities, derivatives, and simulated likelihoods over many observations, alternatives, and draws. Existing DCM…