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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 1051–1060 of 1854 papers

TitleStatusHype
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling SpeakersCode2
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement—0
StyleT2F: Generating Human Faces from Textual Description Using StyleGAN2Code0
Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection—0
Causal Disentanglement with Network Information for Debiased Recommendations—0
An Identity-Preserved Framework for Human Motion Transfer—0
XMP-Font: Self-Supervised Cross-Modality Pre-training for Few-Shot Font Generation—0
Physically Disentangled RepresentationsCode0
Towards efficient representation identification in supervised learningCode0
ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks—0
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