Causal effect identification considers whether an interventional probability distribution can be uniquely determined from a passively observed distribution in a given causal structure.

Afterwards, based onthe enriched representation, we propose one novel graphpointnet module, relyingonthegraphattention blocktodynamically compose and update each point representation within the local point cloud structure.

The variability of what "similar" means in this context, which transformations are allowed, and whether data points themselves or their feature representations

In particular, torsional diffusion does not address the longstanding difficulty that existing cheminformatics methods have with macrocycles--rings with 12 or more atoms that have found several applications in drug discovery [Driggers et al., 2008].

Moreover, when adopting our method to various tasks including part segmentation and standard 2D image classification, our method achieves competitive performance.

However, the leap in performance often comes at the cost of large-scale labeled data.