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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 1121–1130 of 1854 papers

TitleStatusHype
VarietySound: Timbre-Controllable Video to Sound Generation via Unsupervised Information Disentanglement—0
Predicting Human Mobility via Self-supervised Disentanglement Learning—0
3DLatNav: Navigating Generative Latent Spaces for Semantic-Aware 3D Object ManipulationCode0
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors—0
Improved disentangled speech representations using contrastive learning in factorized hierarchical variational autoencoder—0
Disentangling Variational Autoencoders—0
Replacing Language Model for Style TransferCode0
DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation—0
In-memory factorization of holographic perceptual representationsCode0
Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning—0
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