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Found 5 papers, 1 papers with code
Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets
These highpoints make the probabilistic model capable of overcoming challenges brought by the coexistence of multi-structure data and multi-value representations and pave the way for the extension of latent confounders.
CASR: Refining Action Segmentation via Marginalizing Frame-levle Causal Relationships
CASR works out by reducing the difference in the causal adjacency matrix between we constructed and pre-segmentation results of backbone models.
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations
The fusion of causal models with deep learning introducing increasingly intricate data sets, such as the causal associations within images or between textual components, has surfaced as a focal research area.
SSL Framework for Causal Inconsistency between Structures and Representations
The cross-pollination of deep learning and causal discovery has catalyzed a burgeoning field of research seeking to elucidate causal relationships within non-statistical data forms like images, videos, and text.
A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms
Understanding causality helps to structure interventions to achieve specific goals and enables predictions under interventions.
