"disentangled representations" Papers
11 papers found
Conference
Can Diffusion Models Disentangle? A Theoretical Perspective
Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong et al.
NEURIPS 2025arXiv:2504.00220
Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations
Tal Barami, Nimrod Berman, Ilan Naiman et al.
NEURIPS 2025arXiv:2510.17313
2
citations
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel
ICLR 2025arXiv:2407.11249
5
citations
Dreamweaver: Learning Compositional World Models from Pixels
Junyeob Baek, Yi-Fu Wu, Gautam Singh et al.
ICLR 2025arXiv:2501.14174
3
citations
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
ICLR 2025arXiv:2410.06993
3
citations
Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer
XINYUE HU, Zhibin Duan, Bo Chen et al.
ICLR 2025arXiv:2505.22199
3
citations
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
Jianle Sun, Chaoqi Liang, Ran Wei et al.
NEURIPS 2025spotlightarXiv:2510.24987
2
citations
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees
Shaoan Xie, Lingjing Kong, Yujia Zheng et al.
CVPR 2025highlightarXiv:2507.22264
4
citations
DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations
Tianhao Qi, Shancheng Fang, Yanze Wu et al.
CVPR 2024highlightarXiv:2403.06951
90
citations
Disentanglement Learning via Topology
Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.
ICML 2024arXiv:2308.12696
3
citations
Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE
Hao Wu, Huiyuan Wang, kun wang et al.
ICML 2024oral