fulifeng/Causal_Reading_Group
We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
This resource provides a curated and regularly updated list of research papers focused on the intersection of machine learning and causal theory. It helps researchers and practitioners stay current with advancements in applying causal inference to various machine learning subfields. Users can find relevant academic papers to inform their work on topics like causal recommendation systems, computer vision, and natural language processing.
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Use this if you are a researcher, academic, or advanced practitioner working with machine learning and need to understand the latest developments in integrating causal inference into your models and applications.
Not ideal if you are looking for ready-to-use code, datasets for practical implementation, or a basic introduction to either machine learning or causality.
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Mar 03, 2023
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