Cover Image

Improving Hyperbolic Representations via Gromov-Wasserstein Regularization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Yifei, Lee, Wonjun, Zou, Dongmian, Lerman, Gilad
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Monotone Generative Modeling via a Gromov-Monge Embedding
by: Lee, Wonjun, et al.
Published: (2023)

Min Generalized Sliced Gromov Wasserstein: A Scalable Path to Gromov Wasserstein
by: Shahbazi, Ashkan, et al.
Published: (2026)

Understanding Latent Diffusability via Fisher Geometry
by: Gu, Jing, et al.
Published: (2026)

Gromov-Wasserstein-like Distances in the Gaussian Mixture Models Space
by: Salmona, Antoine, et al.
Published: (2023)

Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance
by: Li, Muyang, et al.
Published: (2026)

Shape-of-You: Fused Gromov-Wasserstein Optimal Transport for Semantic Correspondence in-the-Wild
by: Im, Jiin, et al.
Published: (2026)

Disentangled Representation Learning with the Gromov-Monge Gap
by: Uscidda, Théo, et al.
Published: (2024)

Hyperbolic Image-Text Representations
by: Desai, Karan, et al.
Published: (2023)

Procedure Learning via Regularized Gromov-Wasserstein Optimal Transport
by: Mahmood, Syed Ahmed, et al.
Published: (2025)

Maximizing the Position Embedding for Vision Transformers with Global Average Pooling
by: Lee, Wonjun, et al.
Published: (2025)

Learning Structured Representations with Hyperbolic Embeddings
by: Sinha, Aditya, et al.
Published: (2024)

D-TPT: Dimensional Entropy Maximization for Calibrating Test-Time Prompt Tuning in Vision-Language Models
by: Han, Jisu, et al.
Published: (2025)

Improving Adversarial Robustness of Attribution via Implicit Regularization
by: Mehrpanah, Amir, et al.
Published: (2026)

Collaborative Learning with Multiple Foundation Models for Source-Free Domain Adaptation
by: Lee, Huisoo, et al.
Published: (2025)

Variance-Covariance Regularization Improves Representation Learning
by: Zhu, Jiachen, et al.
Published: (2023)

Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering
by: Chen, Tianyi, et al.
Published: (2026)

Hyperbolic Multimodal Representation Learning for Biological Taxonomies
by: Gong, ZeMing, et al.
Published: (2025)

SMaRt: Improving GANs with Score Matching Regularity
by: Xia, Mengfei, et al.
Published: (2023)

Semantic Prompting with Image-Token for Continual Learning
by: Han, Jisu, et al.
Published: (2024)

Ranked Entropy Minimization for Continual Test-Time Adaptation
by: Han, Jisu, et al.
Published: (2025)

On the Role of Discrete Tokenization in Visual Representation Learning
by: Du, Tianqi, et al.
Published: (2024)

Structure by Architecture: Structured Representations without Regularization
by: Leeb, Felix, et al.
Published: (2020)

Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
by: Fan, Jiajun, et al.
Published: (2025)

Improving Chinese Character Representation with Formation Tree
by: Hong, Yang, et al.
Published: (2024)

Out-of-Distribution Segmentation via Wasserstein-Based Evidential Uncertainty
by: Brosch, Arnold, et al.
Published: (2025)

Hyperbolic Optimization
by: Wang, Yanke, et al.
Published: (2025)

CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations
by: Wu, Chengfeng, et al.
Published: (2026)

Stein Discrepancy for Unsupervised Domain Adaptation
by: von Seeger, Anneke, et al.
Published: (2025)

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modeling
by: Srivastava, Akash, et al.
Published: (2020)

Improved Regularization and Robustness for Fine-tuning in Neural Networks
by: Li, Dongyue, et al.
Published: (2021)

Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization
by: Luo, Haocheng, et al.
Published: (2025)

3D Cell Oversegmentation Correction via Geo-Wasserstein Divergence
by: Chen, Peter, et al.
Published: (2025)

When Test-Time Adaptation Meets Self-Supervised Models
by: Han, Jisu, et al.
Published: (2025)

Sharpness-Aware Minimization with Adaptive Regularization for Training Deep Neural Networks
by: Zou, Jinping, et al.
Published: (2024)

Understanding and Improving Training-free Loss-based Diffusion Guidance
by: Shen, Yifei, et al.
Published: (2024)

Improving Forward Compatibility in Class Incremental Learning by Increasing Representation Rank and Feature Richness
by: Kim, Jaeill, et al.
Published: (2024)

PHyCLIP: $\ell_1$-Product of Hyperbolic Factors Unifies Hierarchy and Compositionality in Vision-Language Representation Learning
by: Yoshikawa, Daiki, et al.
Published: (2025)

Soft Equivariance Regularization for Invariant Self-Supervised Learning
by: Lee, Joohyung, et al.
Published: (2026)

Angular Gradient Sign Method: Uncovering Vulnerabilities in Hyperbolic Networks
by: Jo, Minsoo, et al.
Published: (2025)

Disentangled Representation Learning via Modular Compositional Bias
by: Jung, Whie, et al.
Published: (2025)