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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 1526–1550 of 1854 papers

TitleStatusHype
Data-efficient visuomotor policy training using reinforcement learning and generative models—0
Towards Purely Unsupervised Disentanglement of Appearance and Shape for Person Images Generation—0
Learning Disentangled Representations with Latent Variation PredictabilityCode1
MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement—0
Unsupervised Shape and Pose Disentanglement for 3D MeshesCode1
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration—0
Novel View Synthesis on Unpaired Data by Conditional Deformable Variational Auto-EncoderCode0
Unsupervised Heterogeneous Coupling Learning for Categorical Representation—0
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse CodingCode1
Domain2Vec: Domain Embedding for Unsupervised Domain AdaptationCode0
Unsupervised Controllable Generation with Self-Training—0
Online Invariance Selection for Local Feature DescriptorsCode1
LEED: Label-Free Expression Editing via Disentanglement—0
Unsupervised 3D Human Pose Representation with Viewpoint and Pose DisentanglementCode1
Disentanglement of Color and Shape Representations for Continual Learning—0
Pose-aware Adversarial Domain Adaptation for Personalized Facial Expression Recognition—0
Multi-Domain Image Completion for Random Missing Input Data—0
Improving Style-Content Disentanglement in Image-to-Image Translation—0
Low-dimensional Manifold Constrained Disentanglement Network for Metal Artifact Reduction—0
Benefiting Deep Latent Variable Models via Learning the Prior and Removing Latent Regularization—0
Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN—0
Disentangled Graph Collaborative FilteringCode1
Decoder-free Robustness Disentanglement without (Additional) Supervision—0
Graph Neural News Recommendation with Unsupervised Preference DisentanglementCode1
You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural NetworkCode1
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