Graph Contrastive Learning under Heterophily via Graph Filters
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Wenhan, Mirzasoleiman, Baharan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
by: Joshi, Siddharth, et al.
Published: (2023)
by: Joshi, Siddharth, et al.
Published: (2023)
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
by: Yang, Wenhan, et al.
Published: (2023)
by: Yang, Wenhan, et al.
Published: (2023)
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
by: Huang, Jianhao, et al.
Published: (2026)
by: Huang, Jianhao, et al.
Published: (2026)
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
by: Xue, Yihao, et al.
Published: (2023)
by: Xue, Yihao, et al.
Published: (2023)
Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features
by: Joshi, Siddharth, et al.
Published: (2023)
by: Joshi, Siddharth, et al.
Published: (2023)
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks
by: Joshi, Siddharth, et al.
Published: (2024)
by: Joshi, Siddharth, et al.
Published: (2024)
Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
Robust Graph Structure Learning under Heterophily
by: Xie, Xuanting, et al.
Published: (2024)
by: Xie, Xuanting, et al.
Published: (2024)
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
by: Xue, Yihao, et al.
Published: (2022)
by: Xue, Yihao, et al.
Published: (2022)
Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity
by: Joshi, Siddharth, et al.
Published: (2024)
by: Joshi, Siddharth, et al.
Published: (2024)
Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions
by: Xue, Yihao, et al.
Published: (2025)
by: Xue, Yihao, et al.
Published: (2025)
Understanding the Role of Training Data in Test-Time Scaling
by: Javanmard, Adel, et al.
Published: (2025)
by: Javanmard, Adel, et al.
Published: (2025)
Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models
by: Javanmard, Adel, et al.
Published: (2026)
by: Javanmard, Adel, et al.
Published: (2026)
Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, et al.
Published: (2025)
Understanding Heterophily for Graph Neural Networks
by: Wang, Junfu, et al.
Published: (2024)
by: Wang, Junfu, et al.
Published: (2024)
Beyond What Seems Necessary: Hidden Gains from Scaling Training-Time Reasoning Length under Outcome Supervision
by: Xue, Yihao, et al.
Published: (2026)
by: Xue, Yihao, et al.
Published: (2026)
Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, et al.
Published: (2025)
Incorporating Heterophily into Graph Neural Networks for Graph Classification
by: Yang, Jiayi, et al.
Published: (2022)
by: Yang, Jiayi, et al.
Published: (2022)
Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)
by: Zheng, Xin, et al.
Published: (2022)
Exploring Heterophily in Graph-level Tasks
by: Hou, Qinhan, et al.
Published: (2025)
by: Hou, Qinhan, et al.
Published: (2025)
Heterophily-Aware Graph Attention Network
by: Wang, Junfu, et al.
Published: (2023)
by: Wang, Junfu, et al.
Published: (2023)
How Transformers Learn to Plan via Multi-Token Prediction
by: Huang, Jianhao, et al.
Published: (2026)
by: Huang, Jianhao, et al.
Published: (2026)
HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
by: Li, Xinyi, et al.
Published: (2026)
by: Li, Xinyi, et al.
Published: (2026)
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
by: Xue, Yihao, et al.
Published: (2023)
by: Xue, Yihao, et al.
Published: (2023)
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
by: Yang, Yu, et al.
Published: (2023)
by: Yang, Yu, et al.
Published: (2023)
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
by: Yang, Yu, et al.
Published: (2024)
by: Yang, Yu, et al.
Published: (2024)
Investigating the Benefits of Projection Head for Representation Learning
by: Xue, Yihao, et al.
Published: (2024)
by: Xue, Yihao, et al.
Published: (2024)
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
by: Zhu, Jiong, et al.
Published: (2024)
by: Zhu, Jiong, et al.
Published: (2024)
Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
Synthetic Text Generation for Training Large Language Models via Gradient Matching
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, et al.
Published: (2025)
Self-attention Dual Embedding for Graphs with Heterophily
by: Lai, Yurui, et al.
Published: (2023)
by: Lai, Yurui, et al.
Published: (2023)
Cross-Contrastive Clustering for Multimodal Attributed Graphs with Dual Graph Filtering
by: Zheng, Haoran, et al.
Published: (2025)
by: Zheng, Haoran, et al.
Published: (2025)
Data Distribution as a Lever for Guiding Optimizers Toward Superior Generalization in LLMs
by: Gangavarapu, Tushaar, et al.
Published: (2026)
by: Gangavarapu, Tushaar, et al.
Published: (2026)
Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective
by: Lu, Kangkang, et al.
Published: (2024)
by: Lu, Kangkang, et al.
Published: (2024)
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)
by: Cheng, Yao, et al.
Published: (2023)
Structure-Guided Input Graph for GNNs facing Heterophily
by: Tenorio, Victor M., et al.
Published: (2024)
by: Tenorio, Victor M., et al.
Published: (2024)
A Generative Model for Controllable Feature Heterophily in Graphs
by: Wang, Haoyu, et al.
Published: (2025)
by: Wang, Haoyu, et al.
Published: (2025)
Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network
by: Zheng, Yilun, et al.
Published: (2024)
by: Zheng, Yilun, et al.
Published: (2024)
Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap
by: Yang, Wenhan, et al.
Published: (2025)
by: Yang, Wenhan, et al.
Published: (2025)
Disentangling Homophily and Heterophily in Multimodal Graph Clustering
by: Guo, Zhaochen, et al.
Published: (2025)
by: Guo, Zhaochen, et al.
Published: (2025)
Similar Items
-
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
by: Joshi, Siddharth, et al.
Published: (2023) -
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
by: Yang, Wenhan, et al.
Published: (2023) -
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
by: Huang, Jianhao, et al.
Published: (2026) -
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
by: Xue, Yihao, et al.
Published: (2023) -
Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features
by: Joshi, Siddharth, et al.
Published: (2023)