Poster "unsupervised representation learning" Papers

14 papers found

Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification

Zinan Lin, Enshu Liu, Xuefei Ning et al.

NEURIPS 2025arXiv:2509.15591

Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos

Yi Chen, Yuying Ge, Weiliang Tang et al.

ICCV 2025arXiv:2412.04445
22
citations

Unsupervised Federated Graph Learning

Lele Fu, Tianchi Liao, Sheng Huang et al.

NEURIPS 2025

DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation

Zelin Zang, Hao Luo, Kai Wang et al.

ICML 2024arXiv:2309.07909
11
citations

Do Generated Data Always Help Contrastive Learning?

Yifei Wang, Jizhe Zhang, Yisen Wang

ICLR 2024arXiv:2403.12448
35
citations

Do text-free diffusion models learn discriminative visual representations?

Soumik Mukhopadhyay, Matthew Gwilliam, Yosuke Yamaguchi et al.

ECCV 2024arXiv:2311.17921
27
citations

Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing

Ioannis Maniadis Metaxas, Georgios Tzimiropoulos, ioannis Patras

ECCV 2024arXiv:2407.11168
2
citations

Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks

Bjørn Leth Møller, Christian Igel, Kristoffer Wickstrøm et al.

ICML 2024

Hierarchical Correlation Clustering and Tree Preserving Embedding

Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani

CVPR 2024arXiv:2002.07756
9
citations

Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology

Andrew Song, Richard J. Chen, Tong Ding et al.

CVPR 2024arXiv:2405.11643
79
citations

Robustness of Nonlinear Representation Learning

Simon Buchholz, Bernhard Schölkopf

ICML 2024arXiv:2503.15355
6
citations

SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning

Qi Qian, Yuanhong Xu, JUHUA HU

ECCV 2024arXiv:2408.13351

Surface-VQMAE: Vector-quantized Masked Auto-encoders on Molecular Surfaces

Fang Wu, Stan Z Li

ICML 2024

WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer

Kumar Shubham, Aishwarya Jayagopal, Syed Danish et al.

ICML 2024arXiv:2405.04078
5
citations