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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 891–900 of 1854 papers

TitleStatusHype
DSDRNet: Disentangling Representation and Reconstruct Network for Domain Generalization—0
DrFER: Learning Disentangled Representations for 3D Facial Expression Recognition—0
Controllable Face Aging—0
Identifiable Feature Learning for Spatial Data with Nonlinear ICA—0
DreamLight: Towards Harmonious and Consistent Image Relighting—0
Controllable Data Generation Via Iterative Data-Property Mutual Mappings—0
Disentanglement of Emotional Style and Speaker Identity for Expressive Voice Conversion—0
Identity-Disentangled Neural Deformation Model for Dynamic Meshes—0
Intent Disentanglement and Feature Self-supervision for Novel Recommendation—0
DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition—0
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