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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 1091–1100 of 1854 papers

TitleStatusHype
Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image SynthesisCode0
Image-to-Image Translation with Disentangled Latent Vectors for Face Editing—0
Rethinking Video Frame Interpolation from Shutter Mode Induced Degradation—0
ASPnet: Action Segmentation With Shared-Private Representation of Multiple Data Sources—0
Tracking Multiple Deformable Objects in Egocentric Videos—0
Specialist Diffusion: Plug-and-Play Sample-Efficient Fine-Tuning of Text-to-Image Diffusion Models To Learn Any Unseen StyleCode0
Generalized UAV Object Detection via Frequency Domain Disentanglement—0
An Erudite Fine-Grained Visual Classification Model—0
FedPD: Federated Open Set Recognition with Parameter Disentanglement—0
StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer—0
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