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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 1426–1450 of 1854 papers

TitleStatusHype
On the Role of Pre-training for Meta Few-Shot Learning—0
The role of Disentanglement in GeneralisationCode1
Addressing the Topological Defects of Disentanglement—0
Zero-shot Fairness with Invisible Demographics—0
Learning disentangled representations with the Wasserstein Autoencoder—0
GL-Disen: Global-Local disentanglement for unsupervised learning of graph-level representations—0
Private-Shared Disentangled Multimodal VAE for Learning of Hybrid Latent Representations—0
An Assessment of GANs for Identity-related Applications—0
Measuring Disentanglement: A Review of MetricsCode1
Multi-type Disentanglement without Adversarial Training—0
Odd-One-Out Representation LearningCode0
The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement—0
DEAAN: Disentangled Embedding and Adversarial Adaptation Network for Robust Speaker Representation Learning—0
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend ForecastingCode0
Physics-Guided Spoof Trace Disentanglement for Generic Face Anti-Spoofing—0
Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy PreservationCode0
Conditional Generation of Medical Images via Disentangled Adversarial Inference—0
Variational Interaction Information Maximization for Cross-domain DisentanglementCode1
Learning an Animatable Detailed 3D Face Model from In-The-Wild ImagesCode2
Multi-Instrumentalist Net: Unsupervised Generation of Music from Body Movements—0
MakeupBag: Disentangling Makeup Extraction and Application—0
Phonetic Posteriorgrams based Many-to-Many Singing Voice Conversion via Adversarial TrainingCode1
Mutual Information Maximization on Disentangled Representations for Differential Morph Detection—0
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization—0
XHate-999: Analyzing and Detecting Abusive Language Across Domains and Languages—0
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