Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Degree of Interference: A General Framework For Causal Inference Under Interference

Saved in:
Bibliographic Details
Published in:JMLR
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864030190139604992
collection WordPress RSS
FRELIP Feed Integration
container_title JMLR
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:4044
institution FRELIP
journal_source_facet JMLR
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Degree of Interference: A General Framework For Causal Inference Under Interference
Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
subject_facet Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
title Degree of Interference: A General Framework For Causal Inference Under Interference
title_auth Degree of Interference: A General Framework For Causal Inference Under Interference
title_full Degree of Interference: A General Framework For Causal Inference Under Interference
title_fullStr Degree of Interference: A General Framework For Causal Inference Under Interference
title_full_unstemmed Degree of Interference: A General Framework For Causal Inference Under Interference
title_short Degree of Interference: A General Framework For Causal Inference Under Interference
title_sort degree of interference: a general framework for causal inference under interference
topic Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
url http://jmlr.org/papers/v26/24-0119.html