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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 61–70 of 1854 papers

TitleStatusHype
Sign-IDD: Iconicity Disentangled Diffusion for Sign Language ProductionCode1
MixRec: Heterogeneous Graph Collaborative FilteringCode1
Unpaired Multi-Domain Histopathology Virtual Staining using Dual Path Prompted InversionCode1
GoHD: Gaze-oriented and Highly Disentangled Portrait Animation with Rhythmic Poses and Realistic ExpressionCode1
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot LearningCode1
CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial DefenseCode1
ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from VideosCode1
Counterfactual Generative Modeling with Variational Causal InferenceCode1
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion ModelsCode1
Disentangling Textual and Acoustic Features of Neural Speech RepresentationsCode1
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