Diffusion-Assisted Distillation for Self-Supervised Graph Representation Learning with MLPs
Fuente:
arXiv
Saved in:
| Main Authors: | Ahn, Seong Jin, Kim, Myoung-Ho |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Training MLPs on Graphs without Supervision
by: Wang, Zehong, et al.
Published: (2024)
by: Wang, Zehong, et al.
Published: (2024)
Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction
by: Qin, Zongyue, et al.
Published: (2025)
by: Qin, Zongyue, et al.
Published: (2025)
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting
by: Wu, Lirong, et al.
Published: (2024)
by: Wu, Lirong, et al.
Published: (2024)
SimMLP: Training MLPs on Graphs without Supervision
by: Wang, Zehong, et al.
Published: (2024)
by: Wang, Zehong, et al.
Published: (2024)
Data-Driven Self-Supervised Graph Representation Learning
by: Samy, Ahmed E., et al.
Published: (2024)
by: Samy, Ahmed E., et al.
Published: (2024)
Quantifying Representation Reliability in Self-Supervised Learning Models
by: Park, Young-Jin, et al.
Published: (2023)
by: Park, Young-Jin, et al.
Published: (2023)
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025)
by: Xie, Shifeng, et al.
Published: (2025)
ExGRG: Explicitly-Generated Relation Graph for Self-Supervised Representation Learning
by: Naseri, Mahdi, et al.
Published: (2024)
by: Naseri, Mahdi, et al.
Published: (2024)
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
by: Yang, Ling, et al.
Published: (2023)
by: Yang, Ling, et al.
Published: (2023)
Edge-free but Structure-aware: Prototype-Guided Knowledge Distillation from GNNs to MLPs
by: Wu, Taiqiang, et al.
Published: (2023)
by: Wu, Taiqiang, et al.
Published: (2023)
Scalable Graph Self-Supervised Learning
by: Pasand, Ali Saheb, et al.
Published: (2024)
by: Pasand, Ali Saheb, et al.
Published: (2024)
Enhancing Graph Self-Supervised Learning with Graph Interplay
by: Zhao, Xinjian, et al.
Published: (2024)
by: Zhao, Xinjian, et al.
Published: (2024)
RL-BioAug: Label-Efficient Reinforcement Learning for Self-Supervised EEG Representation Learning
by: Lee, Cheol-Hui, et al.
Published: (2026)
by: Lee, Cheol-Hui, et al.
Published: (2026)
The Impact of Semantic Pairs on Self-Supervised Representation Learning
by: Alkhalefi, Mohammad, et al.
Published: (2025)
by: Alkhalefi, Mohammad, et al.
Published: (2025)
Understanding Representation Learnability of Nonlinear Self-Supervised Learning
by: Yang, Ruofeng, et al.
Published: (2024)
by: Yang, Ruofeng, et al.
Published: (2024)
Semi-Supervised Graph Representation Learning with Human-centric Explanation for Predicting Fatty Liver Disease
by: Kim, So Yeon, et al.
Published: (2024)
by: Kim, So Yeon, et al.
Published: (2024)
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 Learning of Disentangled Representations for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2024)
by: Chang, Ching, et al.
Published: (2024)
Multi-Level Knowledge Distillation and Dynamic Self-Supervised Learning for Continual Learning
by: Kim, Taeheon, et al.
Published: (2025)
by: Kim, Taeheon, et al.
Published: (2025)
Graph Representation Learning with Diffusion Generative Models
by: Wesego, Daniel
Published: (2025)
by: Wesego, Daniel
Published: (2025)
A Simple and Scalable Representation for Graph Generation
by: Jang, Yunhui, et al.
Published: (2023)
by: Jang, Yunhui, et al.
Published: (2023)
Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
by: Lee, Jaejun, et al.
Published: (2026)
by: Lee, Jaejun, et al.
Published: (2026)
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
by: Ibrahim, Mark, et al.
Published: (2024)
by: Ibrahim, Mark, et al.
Published: (2024)
Leveraging Auto-Distillation and Generative Self-Supervised Learning in Residual Graph Transformers for Enhanced Recommender Systems
by: Mhedhbi, Eya, et al.
Published: (2025)
by: Mhedhbi, Eya, et al.
Published: (2025)
Constructing Efficient Fact-Storing MLPs for Transformers
by: Dugan, Owen, et al.
Published: (2025)
by: Dugan, Owen, et al.
Published: (2025)
DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning
by: Shi, Zhengyuan, et al.
Published: (2025)
by: Shi, Zhengyuan, et al.
Published: (2025)
Graph Self-Supervised Learning with Learnable Structural and Positional Encodings
by: Wijesinghe, Asiri, et al.
Published: (2025)
by: Wijesinghe, Asiri, et al.
Published: (2025)
Clustering Properties of Self-Supervised Learning
by: Weng, Xi, et al.
Published: (2025)
by: Weng, Xi, et al.
Published: (2025)
Physics Informed Distillation for Diffusion Models
by: Tee, Joshua Tian Jin, et al.
Published: (2024)
by: Tee, Joshua Tian Jin, et al.
Published: (2024)
From Alignment to Prediction: A Study of Self-Supervised Learning and Predictive Representation Learning
by: Dutta, Mintu, et al.
Published: (2026)
by: Dutta, Mintu, et al.
Published: (2026)
PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse
by: Vaaras, Einari, et al.
Published: (2024)
by: Vaaras, Einari, et al.
Published: (2024)
GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
by: Tang, Xiaohang, et al.
Published: (2026)
by: Tang, Xiaohang, et al.
Published: (2026)
Weight-based Decomposition: A Case for Bilinear MLPs
by: Pearce, Michael T., et al.
Published: (2024)
by: Pearce, Michael T., et al.
Published: (2024)
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning
by: Song, Yu, et al.
Published: (2025)
by: Song, Yu, et al.
Published: (2025)
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?
by: Ma, Qian, et al.
Published: (2024)
by: Ma, Qian, et al.
Published: (2024)
PyG-SSL: A Graph Self-Supervised Learning Toolkit
by: Zheng, Lecheng, et al.
Published: (2024)
by: Zheng, Lecheng, et al.
Published: (2024)
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)
by: Jian, Xiangru, et al.
Published: (2024)
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
by: Seo, Hyunjin, et al.
Published: (2025)
by: Seo, Hyunjin, et al.
Published: (2025)
Graffe: Graph Representation Learning via Diffusion Probabilistic Models
by: Chen, Dingshuo, et al.
Published: (2025)
by: Chen, Dingshuo, et al.
Published: (2025)
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
by: Zhang, Zheng, et al.
Published: (2024)
by: Zhang, Zheng, et al.
Published: (2024)
Similar Items
-
Training MLPs on Graphs without Supervision
by: Wang, Zehong, et al.
Published: (2024) -
Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction
by: Qin, Zongyue, et al.
Published: (2025) -
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting
by: Wu, Lirong, et al.
Published: (2024) -
SimMLP: Training MLPs on Graphs without Supervision
by: Wang, Zehong, et al.
Published: (2024) -
Data-Driven Self-Supervised Graph Representation Learning
by: Samy, Ahmed E., et al.
Published: (2024)