Disentangled Representations

CVPR 2024arXiv:2404.01628

#3

Disentangled Prompt Representation for Domain Generalization

De Cheng, Zhipeng Xu, XINYANG JIANG et al.

Learning Equi-angular Representations for Online Continual Learning

Minhyuk Seo, Hyunseo Koh, Wonje Jeung et al.

23

CVPR 2024arXiv:2403.10897

#5

Rethinking Multi-view Representation Learning via Distilled Disentangling

Guanzhou Ke, Bo Wang, Xiao-Li Wang et al.

22

CVPR 2024arXiv:2402.02352

#6

Region-Based Representations Revisited

Michal Shlapentokh-Rothman, Ansel Blume, Yao Xiao et al.

14

ICLR 2025arXiv:2504.16929

#7

A Unifying Framework for Representation Learning

Shaden Alshammari, John Hershey, Axel Feldmann et al.

representation learningloss functionsinformation geometrycontrastive learning+4

12

ICML 2025arXiv:2411.07591

#8

Closed-Loop Unsupervised Representation Disentanglement with $\beta$-VAE Distillation and Diffusion Probabilistic Feedback

Xin Jin, Bohan Li, Baao Xie et al.

Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning

Tim Lenz, Peter Neidlinger, Marta Ligero et al.

FedLF: Layer-Wise Fair Federated Learning

Zibin Pan, Chi Li, Fangchen Yu et al.

Factorized Diffusion Autoencoder for Unsupervised Disentangled Representation Learning

Ancong Wu, Wei-shi Zheng

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries

Chris Kolb, Tobias Weber, Bernd Bischl et al.

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Chenbei Lu, Laixi Shi, Zaiwei Chen et al.

7

ICLR 2025arXiv:2407.11249

#14

Disentangling Representations through Multi-task Learning

Pantelis Vafidis, Aman Bhargava, Antonio Rangel

4

ICCV 2025arXiv:2503.08751

#15

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning

Qi Wang, Zhipeng Zhang, Baao Xie et al.

4

AAAI 2025arXiv:2409.08771

#16

Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning

Zijian Li, Shunxing Fan, Yujia Zheng et al.

In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting

Constantin Philippenko, Kevin Scaman, Laurent Massoulié

AAAI 2025arXiv:2412.20790

#18

Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning

En Fu, Yanyan Hu

ICCV 2025arXiv:2501.04631

#19

Forgetting Through Transforming: Enabling Federated Unlearning via Class-Aware Representation Transformation

Qi Guo, Zhen Tian, Minghao Yao et al.

Disentangled Clothed Avatar Generation with Layered Representation

Weitian Zhang, Yichao Yan, Sijing Wu et al.

ICCV 2025arXiv:2504.20041

#21

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations

Hai Huang, Yan Xia, Sashuai Zhou et al.

Learning Streaming Video Representation via Multitask Training

Yibin Yan, Jilan Xu, Shangzhe Di et al.

unitary representation learninggroup structure discoveryrepresentation theoryfinite groups+4

#23

DIP: Unsupervised Dense In-Context Post-training of Visual Representations

Sophia Sirko-Galouchenko, Spyros Gidaris, Antonin Vobecky et al.

Discovering Group Structures via Unitary Representation Learning

Dongsung Huh

ICLR 2025

2

ICCV 2025arXiv:2411.18651

#25

Verbalized Representation Learning for Interpretable Few-Shot Generalization

Cheng-Fu Yang, Da Yin, Wenbo Hu et al.

ICLR 2024arXiv:2403.06971

#26

A representation-learning game for classes of prediction tasks

Neria Uzan, Nir Weinberger

ICML 2025arXiv:2505.01557

#27

Contextures: Representations from Contexts

Runtian Zhai, Kai Yang, Burak VARICI et al.

AAAI 2025arXiv:2412.08513

#28

REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability

Kristoffer K. Wickstrøm, Thea Brüsch, Michael C. Kampffmeyer et al.

AAAI 2025arXiv:2504.08019

#29

DGFamba: Learning Flow Factorized State Space for Visual Domain Generalization

Qi Bi, Jingjun Yi, Hao Zheng et al.

CVPR 2024arXiv:2402.18152

#30

Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data

Xinting Liao, Weiming Liu, Chaochao Chen et al.

Boosting Neural Representations for Videos with a Conditional Decoder

XINJIE ZHANG, Ren Yang, Dailan He et al.

AAAI 2025arXiv:2408.04963

#32

LiD-FL: Towards List-Decodable Federated Learning

Hong Liu, Liren Shan, Han Bao et al.

AAAI 2025arXiv:2412.15086

#33

SODA: Bottleneck Diffusion Models for Representation Learning

Drew Hudson, Daniel Zoran, Mateusz Malinowski et al.

On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning

Jiayi Chen, Aidong Zhang

Disentangled Partial Label Learning

Wei-Xuan Bao, Yong Rui, Min-Ling Zhang

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation

Haoran Liu, Youzhi Luo, Tianxiao Li et al.

AAAI 2024arXiv:2403.00352

#37

Self-Supervised Representation Learning from Arbitrary Scenarios

Zhaowen Li, Yousong Zhu, Zhiyang Chen et al.

Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning

Ruiqian Nai, Zixin Wen, Ji Li et al.

disentangled representationrepresentation learningabstract visual reasoningdownstream tasks+2

AAAI 2024arXiv:2306.03364

#39

Learning Multi-Task Sparse Representation Based on Fisher Information

Yayu Zhang, Yuhua Qian, Guoshuai Ma et al.

Learning Representations on the Unit Sphere: Investigating Angular Gaussian and Von Mises-Fisher Distributions for Online Continual Learning

Nicolas Michel, Giovanni Chierchia, Romain Negrel et al.

unit sphere representationsangular gaussian distributionvon mises-fisher distributiononline continual learning+2

AAAI 2025arXiv:2412.16581

#41

FedFSL-CFRD: Personalized Federated Few-Shot Learning with Collaborative Feature Representation Disentanglement

Shanfeng Wang, Jianzhao Li, Zaitian Liu et al.

USDRL: Unified Skeleton-Based Dense Representation Learning with Multi-Grained Feature Decorrelation

Wanjiang Weng, Hongsong Wang, Junbo Wang et al.

Transportable Representations for Domain Generalization

Kasra Jalaldoust, Elias Bareinboim

Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning

Da Wang, Lin Li, Wei Wei et al.

Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks

Yeon-Chang Lee, Hojung Shin, Sang-Wook Kim

Deep Disentangled Metric Learning

Jinhee Park, Jisoo Park, Dagyeong Na et al.

Effective and Efficient Representation Learning for Flight Trajectories

Shuo Liu, Wenbin Li, Di Yao et al.

AAAI 2024arXiv:2312.06989

#48

Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks

Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong et al.

AAAI 2025arXiv:2503.09643

#49

FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning

Daoyuan Li, Zuyuan Yang, Shengli Xie

AAAI 2025arXiv:2412.11066

#50

Disentangled Representation Learning with the Gromov-Monge Gap

Théo Uscidda, Luca Eyring, Karsten Roth et al.

Learning Robust and Privacy-Preserving Representations via Information Theory

Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong et al.

AAAI 2025arXiv:2410.06042

#52

Delegation-Relegation for Boolean Matrix Factorization

Florent Avellaneda, Roger Villemaire

Enhancing Evolving Domain Generalization through Dynamic Latent Representations

Binghui Xie, Yongqiang Chen, Jiaqi Wang et al.

Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision

Wonjoon Chang, Dahee Kwon, Jaesik Choi

Weighted Embeddings for Low-Dimensional Graph Representation

Thomas Bläsius, Jean-Pierre von der Heydt, Maximilian Katzmann et al.

CVPR 2025arXiv:2502.21001

#56

Deep Rank-One Tensor Functional Factorization for Multi-Dimensional Data Recovery

Yanyi Li, Xi Zhang, Yisi Luo et al.

Learning with Open-world Noisy Data via Class-independent Margin in Dual Representation Space

Linchao Pan, Can Gao, Jie Zhou et al.

DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations

Guojun Xiong, Gang Yan, Shiqiang Wang et al.

DDDM-VC: Decoupled Denoising Diffusion Models with Disentangled Representation and Prior

Ha-Yeong Choi, Sang-Hoon Lee, Seong-Whan Lee

Boosting Multimodal Learning via Disentangled Gradient Learning

Shicai Wei, Chunbo Luo, Yang Luo

Towards Lossless Implicit Neural Representation via Bit Plane Decomposition

Woo Kyoung Han, Byeonghun Lee, Hyunmin Cho et al.

ICCV 2025arXiv:2509.08940

#62

Discovering Divergent Representations between Text-to-Image Models

Lisa Dunlap, Trevor Darrell, Joseph Gonzalez et al.

ICCV 2025arXiv:2512.24097

#63

Incomplete Multi-View Multi-label Learning via Disentangled Representation and Label Semantic Embedding

Xu Yan, Jun Yin, Jie Wen

Factorized Learning for Temporally Grounded Video-Language Models

Wenzheng Zeng, Difei Gao, Mike Zheng Shou et al.

ICCV 2025arXiv:2408.10789

#65

FLAIR: VLM with Fine-grained Language-informed Image Representations

Rui Xiao, Sanghwan Kim, Iuliana Georgescu et al.

Gradient Extrapolation for Debiased Representation Learning

Ihab Asaad, Maha Shadaydeh, Joachim Denzler

Self-supervised Learning of Hybrid Part-aware 3D Representations of 2D Gaussians and Superquadrics

Zhirui Gao, Renjiao Yi, Yuhang Huang et al.

self-supervised learning3d scene decompositionhybrid 3d representation2d gaussians+4

CVPR 2025arXiv:2412.04077

#68

SeqMvRL: A Sequential Fusion Framework for Multi-view Representation Learning

Ren Wang, Haoliang Sun, Yuxiu Lin et al.

Reducing Class-wise Confusion for Incremental Learning with Disentangled Manifolds

Huitong Chen, Yu Wang, Yan Fan et al.

SINR: Sparsity Driven Compressed Implicit Neural Representations

Dhananjaya Jayasundara, Sudarshan Rajagopalan, Yasiru Ranasinghe et al.

Federated Representation Angle Learning

Liping Yi, Han Yu, Gang Wang et al.

SignRep: Enhancing Self-Supervised Sign Representations

Ryan Wong, Necati Cihan Camgoz, Richard Bowden

SoMA: Singular Value Decomposed Minor Components Adaptation for Domain Generalizable Representation Learning

Seokju Yun, Seunghye Chae, Dongheon Lee et al.

domain generalizationparameter efficient fine tuningsingular value decompositionsemantic segmentation+4

#74

Learning Efficient and Generalizable Human Representation with Human Gaussian Model

Yifan Liu, Shengjun Zhang, Chensheng Dai et al.

Learning in Deep Factor Graphs with Gaussian Belief Propagation

Seth Nabarro, Mark van der Wilk, Andrew Davison

gaussian factor graphsbelief propagationdistributed trainingasynchronous training+3

#76

Learning Graph Representation via Graph Entropy Maximization

Ziheng Sun, Xudong Wang, Chris Ding et al.

graph representation learninggraph entropy maximizationgraph neural networksunsupervised learning+3

#77

Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits

Jiabin Lin, Shana Moothedath, Namrata Vaswani

contextual banditsmulti-task learningrepresentation learningalternating projected gradient descent+3

ICML 2024arXiv:2410.11227

#78

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples

Thomas T. Zhang, Bruce Lee, Ingvar Ziemann et al.

nonlinear representation learningmulti-task learningdependent data analysissample complexity analysis+3

#79

Disentanglement Learning via Topology

Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.

disentangled representationstopological disentanglementunsupervised learningmanifold learning+4

#80

On a Neural Implementation of Brenier's Polar Factorization

Nina Vesseron, Marco Cuturi

polar factorization theoremoptimal transport theoryinput convex neural networksmeasure-preserving maps+4

ICML 2024arXiv:2402.09142

#81

When Representations Align: Universality in Representation Learning Dynamics

Loek van Rossem, Andrew Saxe

representation learning dynamicseffective theoryencoding mapdecoding map+4

NeurIPS 2025arXiv:2510.17313

#82

Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations

Tal Barami, Nimrod Berman, Ilan Naiman et al.

disentangled representationssequential datamulti-factor analysisvision-language models+4

ICLR 2025arXiv:2410.06940

#83

Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Sihyun Yu, Sangkyung Kwak, Huiwon Jang et al.

diffusion transformersrepresentation alignmentgenerative diffusion modelsdenoising networks+3

NeurIPS 2025arXiv:2510.21402

#84

Disentangled Representation Learning via Modular Compositional Bias

whie jung, Dong Hoon Lee, Seunghoon Hong

NeurIPS 2025arXiv:2504.00220

#85

Can Diffusion Models Disentangle? A Theoretical Perspective

Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong et al.

diffusion modelsdisentangled representationslatent variable modelssubspace recovery+4

ECCV 2024arXiv:2408.05599

#86

Sequential Representation Learning via Static-Dynamic Conditional Disentanglement

Mathieu Simon, Pascal Frossard, Christophe De Vleeschouwer

disentangled representation learningsequential data analysisstatic-dynamic disentanglementcausal relationship modeling+4

#87

CFD: Learning Generalized Molecular Representation via Concept-Enhanced Feedback Disentanglement

Aming Wu, Cheng Deng

An Information Criterion for Controlled Disentanglement of Multimodal Data

Chenyu Wang, Sharut Gupta, Xinyi Zhang et al.

Retrieval-based Disentangled Representation Learning with Natural Language Supervision

Jiawei Zhou, Xiaoguang Li, Lifeng Shang et al.

Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference

Khalid OUBLAL, Said Ladjal, David Benhaiem et al.

Online Laplacian-Based Representation Learning in Reinforcement Learning

Maheed Ahmed, Jayanth Bhargav, Mahsa Ghasemi

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data

Thomas T. Zhang, Leonardo Felipe Toso, James Anderson et al.

$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity

Cristian Meo, Louis Mahon, Anirudh Goyal et al.

Federated Representation Learning in the Under-Parameterized Regime

Renpu Liu, Cong Shen, Jing Yang

federated representation learningunder-parameterized regimepersonalized federated learninglow-rank matrix approximation+3

ICLR 2024arXiv:2311.04056

#95

Multi-View Causal Representation Learning with Partial Observability

Dingling Yao, Danru Xu, Sébastien Lachapelle et al.

ICLR 2024arXiv:2305.18484

#96

Compositional Generalization via Forced Rendering of Disentangled Latents

Qiyao Liang, Daoyuan Qian, Liu Ziyin et al.

Neural Fourier Transform: A General Approach to Equivariant Representation Learning

Masanori Koyama, Kenji Fukumizu, Kohei Hayashi et al.

#98

Improved Implicit Neural Representation with Fourier Reparameterized Training

Kexuan Shi, Xingyu Zhou, Shuhang Gu

Robustness of Nonlinear Representation Learning

Simon Buchholz, Bernhard Schölkopf

unsupervised representation learningnonlinear representation learningindependent component analysisnonlinear ica+4

ICML 2025arXiv:2505.20970

#100

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective

Joonkyu Kim, Yejin Kim, Jy-yong Sohn