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Disentanglement

This is an approach to solve a diverse set of tasks in a data efficient manner by disentangling (or isolating ) the underlying structure of the main problem into disjoint parts of its representations. This disentanglement can be done by focussing on the "transformation" properties of the world(main problem)

Papers

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Showing 441–450 of 1854 papers

TitleStatusHype
DSFNet: Learning Disentangled Scenario Factorization for Multi-Scenario Route Ranking—0
A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation—0
U-VAP: User-specified Visual Appearance Personalization via Decoupled Self AugmentationCode1
Review-Based Hyperbolic Cross-Domain RecommendationCode0
Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics—0
WordRobe: Text-Guided Generation of Textured 3D Garments—0
Activity-Biometrics: Person Identification from Daily ActivitiesCode0
Can Large Language Models (or Humans) Disentangle Text?Code0
X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention—0
Defying Imbalanced Forgetting in Class Incremental Learning—0
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