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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 1191–1200 of 1854 papers

TitleStatusHype
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches—0
ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence—0
AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond—0
Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder—0
Attention-based Interactive Disentangling Network for Instance-level Emotional Voice Conversion—0
Attention Hijackers: Detect and Disentangle Attention Hijacking in LVLMs for Hallucination Mitigation—0
AttriHuman-3D: Editable 3D Human Avatar Generation with Attribute Decomposition and Indexing—0
Audio-driven High-resolution Seamless Talking Head Video Editing via StyleGAN—0
AUEditNet: Dual-Branch Facial Action Unit Intensity Manipulation with Implicit Disentanglement—0
A Unified Conditional Disentanglement Framework for Multimodal Brain MR Image Translation—0
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