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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 1651–1700 of 1854 papers

TitleStatusHype
Identity-Disentangled Neural Deformation Model for Dynamic Meshes—0
IdentityDP: Differential Private Identification Protection for Face Images—0
Identity From Here, Pose From There: Self-Supervised Disentanglement and Generation of Objects Using Unlabeled Videos—0
IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction—0
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre—0
iFADIT: Invertible Face Anonymization via Disentangled Identity Transform—0
IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime Talking Head Generation—0
Illumination-Adaptive Person Re-identification—0
Image Denoising via Style Disentanglement—0
Image Disentanglement and Uncooperative Re-Entanglement for High-Fidelity Image-to-Image Translation—0
Image Sentiment Transfer—0
Image Style Transfer and Content-Style Disentanglement—0
Impact of Disentanglement on Pruning Neural Networks—0
Improved disentangled speech representations using contrastive learning in factorized hierarchical variational autoencoder—0
Improved Disentanglement through Aggregated Convolutional Feature Maps—0
Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps—0
Improved Neural Text Attribute Transfer with Non-parallel Data—0
Improving CNN Training using Disentanglement for Liver Lesion Classification in CT—0
Improving Editability in Image Generation with Layer-wise Memory—0
Improving Generative Pre-Training: An In-depth Study of Masked Image Modeling and Denoising Models—0
Improving multi-speaker TTS prosody variance with a residual encoder and normalizing flows—0
Improving Style-Content Disentanglement in Image-to-Image Translation—0
Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modeling—0
Improving the Unsupervised Disentangled Representation Learning with VAE Ensemble—0
Incremental Disentanglement for Environment-Aware Zero-Shot Text-to-Speech Synthesis—0
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations—0
Inductive-Biases for Contrastive Learning of Disentangled Representations—0
Inference-InfoGAN: Inference Independence via Embedding Orthogonal Basis Expansion—0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Information Compensation for Deep Conditional Generative Networks—0
INFORMATION MAXIMIZATION AUTO-ENCODING—0
Information Maximization via Variational Autoencoders for Cross-Domain Recommendation—0
Information Theoretic Regularization for Learning Global Features by Sequential VAE—0
InfoStyler: Disentanglement Information Bottleneck for Artistic Style Transfer—0
InLINE: Inner-Layer Information Exchange for Multi-task Learning on Heterogeneous Graphs—0
Inspecting and Interacting with Meaningful Music Representations using VAE—0
Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement—0
INSURE: An Information Theory Inspired Disentanglement and Purification Model for Domain Generalization—0
Intent Disentanglement and Feature Self-supervision for Novel Recommendation—0
Intent-Interest Disentanglement and Item-Aware Intent Contrastive Learning for Sequential Recommendation—0
Interpretability on clinical analysis from Pattern Disentanglement Insight—0
Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork—0
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges—0
Interpretable Molecular Graph Generation via Monotonic Constraints—0
Interpretable Sentence Representation with Variational Autoencoders and Attention—0
Learning Disentangled Representations for Time Series—0
Interpreting Neural Policies with Disentangled Tree Representations—0
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness—0
Intraoperative Registration by Cross-Modal Inverse Neural Rendering—0
Investigating Disentanglement in a Phoneme-level Speech Codec for Prosody Modeling—0
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