Yujun Yan

Orcid: 0000-0003-3776-4293

According to our database1, Yujun Yan authored at least 29 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks.
CoRR, July, 2025

Judging with Many Minds: Do More Perspectives Mean Less Prejudice?
CoRR, May, 2025

Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift.
CoRR, May, 2025

MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding.
CoRR, February, 2025

Towards Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Spectral Insights into Data-Oblivious Critical Layers in Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks.
CoRR, 2024

How to evaluate your medical time series classification?
CoRR, 2024

Firmware Vulnerability Detection Algorithm Based on Matching Pattern-Specific Numerical Features With Structural Features.
IEEE Access, 2024

Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Heterophily and Graph Neural Networks: Past, Present and Future.
IEEE Data Eng. Bull., 2023

Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective.
CoRR, 2023

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Towards Generalizable Neural Networks for Graph Applications
PhD thesis, 2022

Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks.
Proceedings of the International Conference on 3D Vision, 2021

2020
Benchmarking Semi-supervised Federated Learning.
CoRR, 2020

Generalizing Graph Neural Networks Beyond Homophily.
CoRR, 2020

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neural Execution Engines: Learning to Execute Subroutines.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018
Fast Flow-based Random Walk with Restart in a Multi-query Setting.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018


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