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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 1101–1110 of 1854 papers

TitleStatusHype
Zero-shot Fairness with Invisible Demographics—0
Zero shot framework for satellite image restoration—0
Zero-Shot Generalization of Vision-Based RL Without Data Augmentation—0
Zero-shot Imitation Learning from Demonstrations for Legged Robot Visual Navigation—0
Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning—0
Zero-Shot Style Transfer for Gesture Animation driven by Text and Speech using Adversarial Disentanglement of Multimodal Style Encoding—0
Zero-shot Voice Conversion via Self-supervised Prosody Representation Learning—0
Catch Me If You Can—0
ZS-MSTM: Zero-Shot Style Transfer for Gesture Animation driven by Text and Speech using Adversarial Disentanglement of Multimodal Style Encoding—0
Unified Adversarial Invariance—0
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