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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 1451–1460 of 1854 papers

TitleStatusHype
How Positive Are You: Text Style Transfer using Adaptive Style EmbeddingCode1
Explaining Word Embeddings via Disentangled Representation—0
Learning Disentangled Representations and Group Structure of Dynamical EnvironmentsCode1
ShapeFlow: Learnable Deformation Flows Among 3D Shapes—0
Kinetics-Informed Neural Networks—0
Manipulating Medical Image Translation with Manifold Disentanglement—0
A Metric for Linear Symmetry-Based Disentanglement—0
Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints—0
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder—0
ROME: Robustifying Memory-Efficient NAS via Topology Disentanglement and Gradient Accumulation—0
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