Sorted by date, newest first. Asterisk * indicates equal contribution. Most up-to-date list can be found at Google Scholar
Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective Yinan Huang, Hans Hao-Hsun Hsu, Junran Wang, Bo Dai, Pan Li ICLR 2026 ReALM–GEN Workshop (Spotlight)
A Benchmark on Directed Graph Representation Learning in Hardware Designs Haoyu Wang, Yinan Huang, Nan Wu, Pan Li IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
What Can We Learn from State Space Models for Machine Learning on Graphs? Yinan Huang*, Siqi Miao*, Pan Li IEEE Transactions on Pattern Analysis and Machine Intelligence
Powers of Magnetic Graph Matrix: Fourier Spectrum, Walk Compression, and Applications Yinan Huang, David F Gleich, Pan Li The Proceedings of the National Academy of Sciences (PNAS) 2026
Differentially Private Relational Learning with Entity-level Privacy Guarantees Yinan Huang*, Haoteng Yin*, Eli Chien, Rongzhe Wei, Pan Li NeurIPS 2025
GenAI Copyright Evidence with Operational Meaning Eli Chien*, Amit Saha*, Yinan Huang*, Pan Li ICML Workshop on Reliable and Responsible Foundation Models, 2025
What Are Good Positional Encodings for Directed Graphs? Yinan Huang, Haoyu Wang, Pan Li. ICLR 2025
On the Stability of Expressive Positional Encodings for Graphs Yinan Huang*, William Lu*, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li ICLR 2024
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang NeurIPS 2023
Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang ICLR 2023
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang ICML 2022 (Oral).
Seq-Flow: Efficient Probabilistic Forecasting with Self-Rollout Error Control Yinan Huang, Shitij Govil, Bo Dai, Pan Li arXiv:2610.10440