Publication

Note: * equal contribution

• (Submitted) Zhang, R., Meng, Q., Zhu, R., Wang, Y., Shi, W., Zhang, S., Ma, Z.M., & Liu, T.Y. Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. arXiv preprint arXiv:2302.05104. Link Code

  2024

• Zhang, R.*, Du, X.*, Yan, J., & Zhang, S. (2024). The decoupling concept bottleneck model. IEEE Transactions on Pattern Analysis and Machine Intelligence. Link Code

  2023

• Zhang, R., Meng, Q., & Ma, Z.M. (2023). Deciphering and integrating invariants for neural operator learning with various physical mechanisms. National Science Review. Link Code

  2022

• Zhang, R., Hu, P., Meng, Q., Wang, Y., Zhu, R., Chen, B., Ma, Z.M., & Liu, T.Y. (2022). DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows. Physics of Fluids. Link Code
• Zhang, R., & Zhang, S. (2022). Rethinking influence functions of neural networks in the over-parameterized regime. In Proceedings of the AAAI Conference on Artificial Intelligence (Oral). Link
• Du, X., Yan, J., Zhang, R., & Zha, H. (2022). Cross-network skip-gram embedding for joint network alignment and link prediction. IEEE Transactions on Knowledge and Data Engineering. Link Code