Yunsheng Bai

Orcid: 0000-0003-1623-6184

According to our database¹, Yunsheng Bai authored at least 24 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis.

[BibT_eX]

[DOI]

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

Learning to Compare Hardware Designs for High-Level Synthesis.

[BibT_eX]

[DOI]

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

2023

Neural Network-based Graph-Level Operator Learning

[BibT_eX]

[DOI]

Yunsheng Bai

PhD thesis, 2023

Code Recommendation for Open Source Software Developers.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2023, 2023

Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust GNN-Based Representation Learning for HLS.

[BibT_eX]

[DOI]

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

2022

Subgraph Matching via Query-Conditioned Subgraph Matching Neural Networks and Bi-Level Tree Search.

[BibT_eX]

[DOI]

CoRR, 2022

Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Automated accelerator optimization aided by graph neural networks.

[BibT_eX]

[DOI]

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Improving GNN-based accelerator design automation with meta learning.

[BibT_eX]

[DOI]

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

Enabling Automated FPGA Accelerator Optimization Using Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

GLSearch: Maximum Common Subgraph Detection via Learning to Search.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Multivariate Time Series Classification with Hierarchical Variational Graph Pooling.

[BibT_eX]

[DOI]

CoRR, 2020

Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction.

[BibT_eX]

[DOI]

CoRR, 2020

Hierarchical and Fast Graph Similarity Computation via Graph Coarsening and Deep Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Fast Detection of Maximum Common Subgraph via Deep Q-Learning.

[BibT_eX]

[DOI]

CoRR, 2020

GHashing: Semantic Graph Hashing for Approximate Similarity Search in Graph Databases.

[BibT_eX]

[DOI]

Zongyue Qin

Yunsheng Bai

Yizhou Sun

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity.

[BibT_eX]

[DOI]

CoRR, 2019

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Convolutional Set Matching for Graph Similarity.

[BibT_eX]

[DOI]

CoRR, 2018

Convolutional Neural Networks for Fast Approximation of Graph Edit Distance.

[BibT_eX]

[DOI]

CoRR, 2018

Graph Edit Distance Computation via Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Yunsheng Bai

Timeline

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