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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 1001–1010 of 1854 papers

TitleStatusHype
Disentangling Voice and Content with Self-Supervision for Speaker Recognition—0
Disentanglement with Biological Constraints: A Theory of Functional Cell Types—0
DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model—0
DisMix: Disentangling Mixtures of Musical Instruments for Source-level Pitch and Timbre Manipulation—0
DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation—0
DisProtEdit: Exploring Disentangled Representations for Multi-Attribute Protein Editing—0
Distortion-Disentangled Contrastive Learning—0
Distribution Regularized Self-Supervised Learning for Domain Adaptation of Semantic Segmentation—0
Diverse Image Style Transfer via Invertible Cross-Space Mapping—0
D-LORD for Motion Stylization—0
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