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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 321–330 of 1854 papers

TitleStatusHype
Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized ExpertsCode1
Neural Video Portrait Relighting in Real-time via Consistency ModelingCode1
Speech Resynthesis from Discrete Disentangled Self-Supervised RepresentationsCode1
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and TranslationCode1
Scaling-up Disentanglement for Image TranslationCode1
Adversarial Graph DisentanglementCode1
VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of ExpertsCode1
ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual ScansCode1
Image-to-image Translation via Hierarchical Style DisentanglementCode1
Representation Disentanglement for Multi-modal brain MR AnalysisCode1
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