Disentangled Representation Learning with Transmitted Information Bottleneck
Fuente:
arXiv
Saved in:
| Main Authors: | Dang, Zhuohang, Luo, Minnan, Jia, Chengyou, Dai, Guang, Wang, Jihong, Chang, Xiaojun, Wang, Jingdong |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Disentangled Noisy Correspondence Learning
by: Dang, Zhuohang, et al.
Published: (2024)
by: Dang, Zhuohang, et al.
Published: (2024)
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement
by: Jia, Chengyou, et al.
Published: (2023)
by: Jia, Chengyou, et al.
Published: (2023)
SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation
by: Jia, Chengyou, et al.
Published: (2023)
by: Jia, Chengyou, et al.
Published: (2023)
Multi-Modal Dataset Distillation in the Wild
by: Dang, Zhuohang, et al.
Published: (2025)
by: Dang, Zhuohang, et al.
Published: (2025)
From Ideal to Real: Unified and Data-Efficient Dense Prediction for Real-World Scenarios
by: Xia, Changliang, et al.
Published: (2025)
by: Xia, Changliang, et al.
Published: (2025)
Flow-Factory: A Unified Framework for Reinforcement Learning in Flow-Matching Models
by: Ping, Bowen, et al.
Published: (2026)
by: Ping, Bowen, et al.
Published: (2026)
PaCo-RL: Advancing Reinforcement Learning for Consistent Image Generation with Pairwise Reward Modeling
by: Ping, Bowen, et al.
Published: (2025)
by: Ping, Bowen, et al.
Published: (2025)
$\mathrm{D}^\mathrm{3}$-Predictor: Noise-Free Deterministic Diffusion for Dense Prediction
by: Xia, Changliang, et al.
Published: (2025)
by: Xia, Changliang, et al.
Published: (2025)
ChatGen: Automatic Text-to-Image Generation From FreeStyle Chatting
by: Jia, Chengyou, et al.
Published: (2024)
by: Jia, Chengyou, et al.
Published: (2024)
Why Settle for One? Text-to-ImageSet Generation and Evaluation
by: Jia, Chengyou, et al.
Published: (2025)
by: Jia, Chengyou, et al.
Published: (2025)
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval
by: Han, Haochen, et al.
Published: (2024)
by: Han, Haochen, et al.
Published: (2024)
Learning Decomposable and Debiased Representations via Attribute-Centric Information Bottlenecks
by: Hong, Jinyung, et al.
Published: (2024)
by: Hong, Jinyung, et al.
Published: (2024)
Unsqueeze [CLS] Bottleneck to Learn Rich Representations
by: Su, Qing, et al.
Published: (2024)
by: Su, Qing, et al.
Published: (2024)
Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
by: Li, Liuzhuozheng, et al.
Published: (2026)
by: Li, Liuzhuozheng, et al.
Published: (2026)
Mitigating Spurious Background Bias in Multimedia Recognition with Disentangled Concept Bottlenecks
by: Huang, Gaoxiang, et al.
Published: (2025)
by: Huang, Gaoxiang, et al.
Published: (2025)
Disentangled Representation Learning with the Gromov-Monge Gap
by: Uscidda, Théo, et al.
Published: (2024)
by: Uscidda, Théo, et al.
Published: (2024)
Disentangled Representation Learning via Modular Compositional Bias
by: Jung, Whie, et al.
Published: (2025)
by: Jung, Whie, et al.
Published: (2025)
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
by: Xie, Baao, et al.
Published: (2024)
by: Xie, Baao, et al.
Published: (2024)
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
by: Wang, Ying, et al.
Published: (2023)
by: Wang, Ying, et al.
Published: (2023)
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
by: Hsu, Kyle, et al.
Published: (2024)
by: Hsu, Kyle, et al.
Published: (2024)
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
by: Hahm, Jaehoon, et al.
Published: (2024)
by: Hahm, Jaehoon, et al.
Published: (2024)
WaterVIB: Learning Minimal Sufficient Watermark Representations via Variational Information Bottleneck
by: He, Haoyuan, et al.
Published: (2026)
by: He, Haoyuan, et al.
Published: (2026)
Maximizing Information in Domain-Invariant Representation Improves Transfer Learning
by: Li, Adrian Shuai, et al.
Published: (2023)
by: Li, Adrian Shuai, et al.
Published: (2023)
Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization
by: Cheng, De, et al.
Published: (2025)
by: Cheng, De, et al.
Published: (2025)
DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks
by: Cui, Wei, et al.
Published: (2025)
by: Cui, Wei, et al.
Published: (2025)
Unsupervised Learning of Disentangled Representations from Video
by: Denton, Remi, et al.
Published: (2017)
by: Denton, Remi, et al.
Published: (2017)
Explicitly Disentangled Representations in Object-Centric Learning
by: Majellaro, Riccardo, et al.
Published: (2024)
by: Majellaro, Riccardo, et al.
Published: (2024)
Visual Imitation Learning with Calibrated Contrastive Representation
by: Wang, Yunke, et al.
Published: (2024)
by: Wang, Yunke, et al.
Published: (2024)
Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment
by: Jia, Haozhe, et al.
Published: (2026)
by: Jia, Haozhe, et al.
Published: (2026)
Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modeling
by: Srivastava, Akash, et al.
Published: (2020)
by: Srivastava, Akash, et al.
Published: (2020)
The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results
by: Chen, Qiuyu, et al.
Published: (2025)
by: Chen, Qiuyu, et al.
Published: (2025)
MoEGCL: Mixture of Ego-Graphs Contrastive Representation Learning for Multi-View Clustering
by: Zhu, Jian, et al.
Published: (2025)
by: Zhu, Jian, et al.
Published: (2025)
Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning
by: Wang, Qi, et al.
Published: (2025)
by: Wang, Qi, et al.
Published: (2025)
Multimodal Structure Learning: Disentangling Shared and Specific Topology via Cross-Modal Graphical Lasso
by: Wang, Fei, et al.
Published: (2026)
by: Wang, Fei, et al.
Published: (2026)
Assessing Model Generalization in Vicinity
by: Liu, Yuchi, et al.
Published: (2024)
by: Liu, Yuchi, et al.
Published: (2024)
Symbolic Disentangled Representations for Images
by: Korchemnyi, Alexandr, et al.
Published: (2024)
by: Korchemnyi, Alexandr, et al.
Published: (2024)
Denoising Multi-Beta VAE: Representation Learning for Disentanglement and Generation
by: Uppal, Anshuk, et al.
Published: (2025)
by: Uppal, Anshuk, et al.
Published: (2025)
Sequential Representation Learning via Static-Dynamic Conditional Disentanglement
by: Simon, Mathieu Cyrille, et al.
Published: (2024)
by: Simon, Mathieu Cyrille, et al.
Published: (2024)
Domain Generalization in-the-Wild: Disentangling Classification from Domain-Aware Representations
by: Son, Ha Min, et al.
Published: (2025)
by: Son, Ha Min, et al.
Published: (2025)
L-VAE: Variational Auto-Encoder with Learnable Beta for Disentangled Representation
by: Ozcan, Hazal Mogultay, et al.
Published: (2025)
by: Ozcan, Hazal Mogultay, et al.
Published: (2025)
Similar Items
-
Disentangled Noisy Correspondence Learning
by: Dang, Zhuohang, et al.
Published: (2024) -
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement
by: Jia, Chengyou, et al.
Published: (2023) -
SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation
by: Jia, Chengyou, et al.
Published: (2023) -
Multi-Modal Dataset Distillation in the Wild
by: Dang, Zhuohang, et al.
Published: (2025) -
From Ideal to Real: Unified and Data-Efficient Dense Prediction for Real-World Scenarios
by: Xia, Changliang, et al.
Published: (2025)