Summary: A new method developed by researchers allows scientists to identify unique, redundant, and synergistic causality, ...

A novel machine learning model called Temporal Autoencoders for Causal Inference (TACI) accurately detects changing cause-and ...

随着AI技术的快速发展，大语言模型（LLM）如ChatGPT、LLaMA等成为了研究和应用的热点。然而，这些模型在解决复杂问题时常常依赖统计相关性，无法有效捕捉因果关系，因此面临幻觉、偏见等局限性。如何将因果性融入LLM，构建更智能的AI系统，成为当前研究的重要课题。在即将举行的「因果科学与大语言模型读书会」中，来自浙江大学的况琨教授和吴安鹏同学将分享其最新综述《Causality for Lar ...

A new computational method can identify how cause-and-effect relationships ebb and flow over time in dynamic real-life systems such as the brain.

An extensive study utilizing the UK Biobank explores the impact of lifetime cannabis use on brain structure and function, ...

在机器学习领域，特征工程是提升模型性能的关键步骤。它涉及选择、创建和转换输入变量，以构建最能代表底层问题结构的特征集。然而，在许多实际应用中，仅仅依靠统计相关性进行特征选择可能导致误导性的结果，特别是在我们需要理解因果关系的场景中。因果推断方法为特征 ...

Researchers using machine learning discovered that variations in microbial load in the gut, influenced by age, sex, diet, and ...

However, the researchers noted that this study was an observational study and, therefore, can only address associations and ...

Check if you have access via personal or institutional login This book, geared toward academic researchers and graduate students, brings together research on all facets of how time and causality ...

The team acknowledges limitations to the work. Because the analysis was based only on associations, they were not able to establish a clear direction of causality, nor could they provide mechanistic ...