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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 51–60 of 1854 papers

TitleStatusHype
3D Face Modeling via Weakly-supervised Disentanglement Network joint Identity-consistency PriorCode1
Continuous Melody Generation via Disentangled Short-Term Representations and Structural ConditionsCode1
Contrastive Learning Inverts the Data Generating ProcessCode1
Adversarial Continual Learning for Multi-Domain Hippocampal SegmentationCode1
Conditional Mutual Information for Disentangled Representations in Reinforcement LearningCode1
A robust estimator of mutual information for deep learning interpretabilityCode1
Architecture Disentanglement for Deep Neural NetworksCode1
Arbitrary Style Transfer via Multi-Adaptation NetworkCode1
Structured Multi-Track Accompaniment Arrangement via Style Prior ModellingCode1
Continual Learning for Text Classification with Information Disentanglement Based RegularizationCode1
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