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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 1801–1825 of 1854 papers

TitleStatusHype
Metric Learning vs Classification for Disentangled Music Representation Learning—0
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer—0
Mimic: Speaking Style Disentanglement for Speech-Driven 3D Facial Animation—0
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation—0
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness—0
Mixup Barcodes: Quantifying Geometric-Topological Interactions between Point Clouds—0
MLSD-GAN -- Generating Strong High Quality Face Morphing Attacks using Latent Semantic Disentanglement—0
MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation—0
Model-based occlusion disentanglement for image-to-image translation—0
Model Debiasing via Gradient-based Explanation on Representation—0
Modeling Human Driving Behavior through Generative Adversarial Imitation Learning—0
Modular Representations for Weak Disentanglement—0
Monte Carlo Planning for Stochastic Control on Constrained Markov Decision Processes—0
MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation—0
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns—0
MotionMaster: Training-free Camera Motion Transfer For Video Generation—0
MotionZero:Exploiting Motion Priors for Zero-shot Text-to-Video Generation—0
MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain—0
Move Anything with Layered Scene Diffusion—0
MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement—0
MSM-VC: High-fidelity Source Style Transfer for Non-Parallel Voice Conversion by Multi-scale Style Modeling—0
Multi-Domain Image Completion for Random Missing Input Data—0
Multi-domain Unsupervised Image-to-Image Translation with Appearance Adaptive Convolution—0
Multi-input Architecture and Disentangled Representation Learning for Multi-dimensional Modeling of Music Similarity—0
Multi-Instrumentalist Net: Unsupervised Generation of Music from Body Movements—0
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