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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 341–350 of 1854 papers

TitleStatusHype
MUSA: Multi-lingual Speaker Anonymization via Serial Disentanglement—0
ColorwAI: Generative Colorways of Textiles through GAN and Diffusion Disentanglement—0
Features Reconstruction Disentanglement Cloth-Changing Person Re-Identification—0
On Large Language Model Continual UnlearningCode1
Label-anticipated Event Disentanglement for Audio-Visual Video Parsing—0
Boosting Medical Image Synthesis via Registration-guided Consistency and Disentanglement Learning—0
Disentangled Representation Learning with the Gromov-Monge Gap—0
SaMoye: Zero-shot Singing Voice Conversion Model Based on Feature Disentanglement and EnhancementCode2
ColorPeel: Color Prompt Learning with Diffusion Models via Color and Shape DisentanglementCode2
Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task ArithmeticCode1
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