Saved in:
| Main Author: | Huang, Yongchao |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2026
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.19228176 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Gaussian Joint Embeddings For Self-Supervised Representation Learning
by: Huang, Yongchao
Published: (2026)
by: Huang, Yongchao
Published: (2026)
BiJEPA: Bi-directional Joint Embedding Predictive Architecture for Symmetric Representation Learning
by: Huang, Yongchao
Published: (2026)
by: Huang, Yongchao
Published: (2026)
VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
by: Huang, Yongchao
Published: (2026)
by: Huang, Yongchao
Published: (2026)
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025)
by: Xie, Shifeng, et al.
Published: (2025)
S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning
by: Manová, Alžběta, et al.
Published: (2023)
by: Manová, Alžběta, et al.
Published: (2023)
Sampling via Gaussian Mixture Approximations
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Soft Clustering Anchors for Self-Supervised Speech Representation Learning in Joint Embedding Prediction Architectures
by: Ioannides, Georgios, et al.
Published: (2026)
by: Ioannides, Georgios, et al.
Published: (2026)
Negative-Free Self-Supervised Gaussian Embedding of Graphs
by: Liu, Yunhui, et al.
Published: (2024)
by: Liu, Yunhui, et al.
Published: (2024)
Predict, Cluster, Refine: A Joint Embedding Predictive Self-Supervised Framework for Graph Representation Learning
by: Srinivasan, Srinitish, et al.
Published: (2025)
by: Srinivasan, Srinitish, et al.
Published: (2025)
Knowledge, Rules and Their Embeddings: Two Paths towards Neuro-Symbolic JEPA
by: Huang, Yongchao, et al.
Published: (2026)
by: Huang, Yongchao, et al.
Published: (2026)
On the Importance of Embedding Norms in Self-Supervised Learning
by: Draganov, Andrew, et al.
Published: (2025)
by: Draganov, Andrew, et al.
Published: (2025)
RL as Regressor: A Reinforcement Learning Approach for Function Approximation
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Self-Supervised Learning with Gaussian Processes
by: Duan, Yunshan, et al.
Published: (2025)
by: Duan, Yunshan, et al.
Published: (2025)
Maximizing Data Efficiency for Cross-Lingual TTS Adaptation by Self-Supervised Representation Mixing and Embedding Initialization
by: Huang, Wei-Ping, et al.
Published: (2024)
by: Huang, Wei-Ping, et al.
Published: (2024)
Graph-level Representation Learning with Joint-Embedding Predictive Architectures
by: Skenderi, Geri, et al.
Published: (2023)
by: Skenderi, Geri, et al.
Published: (2023)
Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction
by: Wu, Jiele, et al.
Published: (2026)
by: Wu, Jiele, et al.
Published: (2026)
Self-Supervised Representation Learning for Geospatial Objects: A Survey
by: Chen, Yile, et al.
Published: (2024)
by: Chen, Yile, et al.
Published: (2024)
Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods
by: Otero, Daniel, et al.
Published: (2024)
by: Otero, Daniel, et al.
Published: (2024)
Semantic Concentration for Self-Supervised Dense Representations Learning
by: Wen, Peisong, et al.
Published: (2025)
by: Wen, Peisong, et al.
Published: (2025)
Self-Supervised Graph Embedding Clustering
by: Li, Fangfang, et al.
Published: (2024)
by: Li, Fangfang, et al.
Published: (2024)
Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning
by: Van Assel, Hugues, et al.
Published: (2025)
by: Van Assel, Hugues, et al.
Published: (2025)
Self-Supervised Representation Learning as Mutual Information Maximization
by: Sabby, Akhlaqur Rahman, et al.
Published: (2025)
by: Sabby, Akhlaqur Rahman, et al.
Published: (2025)
On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
by: Wang, Bokun, et al.
Published: (2024)
by: Wang, Bokun, et al.
Published: (2024)
Self-Supervised Pre-Training with Joint-Embedding Predictive Architecture Boosts ECG Classification Performance
by: Weimann, Kuba, et al.
Published: (2024)
by: Weimann, Kuba, et al.
Published: (2024)
Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture -- Bridging Predictive and Generative Self-Supervised Learning
by: Gögl, Moritz, et al.
Published: (2026)
by: Gögl, Moritz, et al.
Published: (2026)
Understanding Self-Supervised Learning via Gaussian Mixture Models
by: Bansal, Parikshit, et al.
Published: (2024)
by: Bansal, Parikshit, et al.
Published: (2024)
Neural Bayesian Sequential Routing
by: Huang, Yongchao
Published: (2026)
by: Huang, Yongchao
Published: (2026)
LLM-Prior: A Framework for Knowledge-Driven Prior Elicitation and Aggregation
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Probabilistic and reinforced mining of association rules
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
SparseJEPA: Sparse Representation Learning of Joint Embedding Predictive Architectures
by: Hartman, Max, et al.
Published: (2025)
by: Hartman, Max, et al.
Published: (2025)
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
by: Kim, Sunwoo, et al.
Published: (2024)
by: Kim, Sunwoo, et al.
Published: (2024)
Understanding Representation Learnability of Nonlinear Self-Supervised Learning
by: Yang, Ruofeng, et al.
Published: (2024)
by: Yang, Ruofeng, et al.
Published: (2024)
The Impact of Semantic Pairs on Self-Supervised Representation Learning
by: Alkhalefi, Mohammad, et al.
Published: (2025)
by: Alkhalefi, Mohammad, et al.
Published: (2025)
Quantifying Representation Reliability in Self-Supervised Learning Models
by: Park, Young-Jin, et al.
Published: (2023)
by: Park, Young-Jin, et al.
Published: (2023)
Data-Driven Self-Supervised Graph Representation Learning
by: Samy, Ahmed E., et al.
Published: (2024)
by: Samy, Ahmed E., et al.
Published: (2024)
On Linear Separation Capacity of Self-Supervised Representation Learning
by: Wang, Shulei
Published: (2023)
by: Wang, Shulei
Published: (2023)
Training data membership inference via Gaussian process meta-modeling: a post-hoc analysis approach
by: Huang, Yongchao, et al.
Published: (2025)
by: Huang, Yongchao, et al.
Published: (2025)
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual Representations
by: Baharoon, Mohammed, et al.
Published: (2024)
by: Baharoon, Mohammed, et al.
Published: (2024)
High-Performance Self-Supervised Learning by Joint Training of Flow Matching
by: Ukita, Kosuke, et al.
Published: (2025)
by: Ukita, Kosuke, et al.
Published: (2025)
Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning
by: Dai, Bo, et al.
Published: (2026)
by: Dai, Bo, et al.
Published: (2026)
Similar Items
-
Gaussian Joint Embeddings For Self-Supervised Representation Learning
by: Huang, Yongchao
Published: (2026) -
BiJEPA: Bi-directional Joint Embedding Predictive Architecture for Symmetric Representation Learning
by: Huang, Yongchao
Published: (2026) -
VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
by: Huang, Yongchao
Published: (2026) -
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025) -
S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning
by: Manová, Alžběta, et al.
Published: (2023)