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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 811–820 of 1854 papers

TitleStatusHype
Auto-Encoding Total Correlation Explanation—0
EASY: Emotion-aware Speaker Anonymization via Factorized Distillation—0
Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains—0
Generating Furry Cars: Disentangling Object Shape & Appearance across Multiple Domains—0
Generating Geological Facies Models with Fidelity to Diversity and Statistics of Training Images using Improved Generative Adversarial Networks—0
Generating Multi-Sentence Abstractive Summaries of Interleaved Texts—0
Correcting Flaws in Common Disentanglement Metrics—0
All-In-One: Facial Expression Transfer, Editing and Recognition Using A Single Network—0
Dynamic Causal Disentanglement Model for Dialogue Emotion Detection—0
Dynamic Activation with Knowledge Distillation for Energy-Efficient Spiking NN Ensembles—0
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