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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 1781–1790 of 1854 papers

TitleStatusHype
Unsupervised Domain-Specific Deblurring via Disentangled RepresentationsCode0
FAVAE: Sequence Disentanglement using Information Bottleneck PrincipleCode0
Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image TranslationCode0
Relevance Factor VAE: Learning and Identifying Disentangled FactorsCode0
Embodied Multimodal Multitask Learning—0
Foreground-aware Image Inpainting—0
Learning a Generative Model of Cancer MetastasisCode0
Image Disentanglement and Uncooperative Re-Entanglement for High-Fidelity Image-to-Image Translation—0
Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation—0
A Style-Based Generator Architecture for Generative Adversarial NetworksCode2
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