@inproceedings{chen2024mixsat,title={MixSATGEN: Learning Graph Mixing for SAT Instance Generation},author={Chen*, Xinyan and Li*, Yang and Wang, Runzhong and Yan, Junchi},booktitle={The Twelfth International Conference on Learning Representations},year={2024},}
arXiv
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications
Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, and
23 more authors
@article{li2024machine,title={Machine Learning Insides OptVerse AI Solver: Design Principles and Applications},author={Li, Xijun and Zhu, Fangzhou and Zhen, Hui-Ling and Luo, Weilin and Lu, Meng and Huang, Yimin and Fan, Zhenan and Zhou, Zirui and Kuang, Yufei and Wang, Zhihai and Geng, Zijie and Li, Yang and Liu, Haoyang and An, Zhiwu and Yang, Muming and Li, Jianshu and Wang, Jie and Yan, Junchi and Sun, Defeng and Zhong, Tao and Zhang, Yong and Zeng, Jia and Yuan, Mingxuan and Hao, Jianye and Yao, Jun and Mao, Kun},year={2024},journal={arXiv preprint},}
arXiv
Molecule Generation for Drug Design: a Graph Learning Perspective
Nianzu Yang, Huaijin Wu, Kaipeng Zeng, and
2 more authors
@article{yang2024molecule,title={Molecule Generation for Drug Design: a Graph Learning Perspective},author={Yang, Nianzu and Wu, Huaijin and Zeng, Kaipeng and Li, Yang and Yan, Junchi},year={2024},journal={arXiv preprint},}
2023
arXiv
Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems
Haoyu Geng, Han Ruan, Runzhong Wang, and
4 more authors
@article{geng2023rethinking,title={Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems},author={Geng, Haoyu and Ruan, Han and Wang, Runzhong and Li, Yang and Wang, Yang and Chen, Lei and Yan, Junchi},journal={arXiv preprint},year={2023}}
NeurIPS
T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
Yang Li, Jinpei Guo, Runzhong Wang, and
1 more author
In Advances in Neural Information Processing Systems, 2023
@inproceedings{li2023t2tco,title={T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization},author={Li, Yang and Guo, Jinpei and Wang, Runzhong and Yan, Junchi},booktitle={Advances in Neural Information Processing Systems},year={2023}}
SIGKDD
HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline
Yang Li, Xinyan Chen, Wenxuan Guo, and
6 more authors
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
@inproceedings{li2023hardsatgen,title={HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline},author={Li, Yang and Chen, Xinyan and Guo, Wenxuan and Li, Xijun and Luo, Wanqian and Huang, Junhua and Zhen, Hui-Ling and Yuan, Mingxuan and Yan, Junchi},booktitle={Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},year={2023}}
IJCAI
IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse
Yang Li*, Liangliang Shi*, and Junchi Yan
In Proceedings of the 32nd International Joint Conference on Artificial Intelligence, 2023
@inproceedings{iid2023li,author={Li*, Yang and Shi*, Liangliang and Yan, Junchi},booktitle={Proceedings of the 32nd International Joint Conference on Artificial Intelligence},title={IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse},year={2023}}
2022
NeurIPSSpotlight (top 5%)
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space
Yang Li, Yichuan Mo, Liangliang Shi, and
1 more author
In Advances in Neural Information Processing Systems, 2022
@inproceedings{li2022improving,author={Li, Yang and Mo, Yichuan and Shi, Liangliang and Yan, Junchi},booktitle={Advances in Neural Information Processing Systems},editor={Koyejo, S. and Mohamed, S. and Agarwal, A. and Belgrave, D. and Cho, K. and Oh, A.},pages={8868--8881},publisher={Curran Associates, Inc.},title={Improving Generative Adversarial Networks via Adversarial Learning in Latent Space},volume={35},year={2022}}
NeurIPS
The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design
Ruoyu Cheng, Xianglong Lyu, Yang Li, and
3 more authors
In Advances in Neural Information Processing Systems, 2022
@inproceedings{NEURIPS2022_a8b8c1ad,author={Cheng, Ruoyu and Lyu, Xianglong and Li, Yang and Ye, Junjie and Hao, Jianye and Yan, Junchi},booktitle={Advances in Neural Information Processing Systems},editor={Koyejo, S. and Mohamed, S. and Agarwal, A. and Belgrave, D. and Cho, K. and Oh, A.},pages={26350--26362},publisher={Curran Associates, Inc.},title={The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design},volume={35},year={2022}}
@article{li2022kissat,title={Kissat Adaptive Restart, Kissat Cfexp: Adaptive Restart Policy and Variable Scoring Improvement},author={Li, Yang and Jia, Yuqi and Luo, Wanqian and Zhen, Hui-Ling and Li, Xijun and Yuan, Mingxuan and Yan, Junchi},journal={Proceedings of SAT Competition},year={2022}}