Given a set of experiments in which varying subsets of observed variables are subject to intervention, we consider the problem of identifiability of causal models exhibiting late...
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoy...
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
The estimation of linear causal models (also known as structural equation models) from data is a well-known problem which has received much attention in the past. Most previous wo...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
Recognition using appearance features is confounded by
phenomena that cause images of the same object to look different,
or images of different objects to look the same. This
ma...
Ali Farhadi, Mostafa Kamali Tabrizi, Ian Endres, D...
A fundamental question in causal inference is whether it is possible to reliably infer the manipulation effects from observational data. There are a variety of senses of asymptot...