Conformal Prediction：理论与新挑战的统一综述
Conformal Prediction: a Unified Review of Theory and New Challenges
AI总结：
本文对无分布非参数预测方法Conformal Prediction展开统一综述，梳理其理论基础，同时列举该方法的前沿发展与适配方向，为相关领域研究提供系统参考。
摘要：
在这项工作中，我们对Conformal Prediction（共形预测）的基本理念与最新进展进行了综述——这是一种创新的无分布、非参数预测方法，基于极少假设，能够以十分直接的方式生成在有限样本情形下也具备统计意义有效性的预测集。本文展开的深入讨论涵盖了Conformal Prediction的理论基础，随后进一步列举了该原始思路的更高级发展与适配方案。
英文摘要：
In this work we provide a review of basic ideas and novel developments about Conformal Prediction -- an innovative distribution-free, non-parametric forecasting method, based on minimal assumptions -- that is able to yield in a very straightforward way predictions sets that are valid in a statistical sense also in in the finite sample case. The in-depth discussion provided in the paper covers the theoretical underpinnings of Conformal Prediction, and then proceeds to list the more advanced developments and adaptations of the original idea.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
