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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 1376–1400 of 1854 papers

TitleStatusHype
WordRobe: Text-Guided Generation of Textured 3D Garments—0
XHate-999: Analyzing and Detecting Abusive Language Across Domains and Languages—0
XMP-Font: Self-Supervised Cross-Modality Pre-training for Few-Shot Font Generation—0
X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention—0
Y-GAN: Learning Dual Data Representations for Efficient Anomaly Detection—0
You Talking to Me? A Corpus and Algorithm for Conversation Disentanglement—0
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
ZS-MSTM: Zero-Shot Style Transfer for Gesture Animation driven by Text and Speech using Adversarial Disentanglement of Multimodal Style Encoding—0
Learning Interpretable Disentangled Representations using Adversarial VAEs—0
Learning long-term music representations via hierarchical contextual constraints—0
Learning Multi-Modal Brain Tumor Segmentation from Privileged Semi-Paired MRI Images with Curriculum Disentanglement Learning—0
An Identifiable Double VAE For Disentangled Representations—0
Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing—0
Learning Robust Representation for Joint Grading of Ophthalmic Diseases via Adaptive Curriculum and Feature Disentanglement—0
Learning Shape Representations for Clothing Variations in Person Re-Identification—0
Learning Source Disentanglement in Neural Audio Codec—0
Learning Sparse Disentangled Representations for Multimodal Exclusion Retrieval—0
Learning Sparse Latent Representations with the Deep Copula Information Bottleneck—0
Learning Speaker-Invariant Visual Features for Lipreading—0
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