Publication

Note: * equal contribution

2025

Zhang, R., Meng, Q., Zhu, R., Wang, Y., Shi, W., Zhang, S., Ma, Z.M., & Liu, T.Y. (2025). Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Link Code
Zhang, R.*, Du, X.*, Yan, J., & Zhang, S. (2025). The decoupling concept bottleneck model. IEEE Transactions on Pattern Analysis and Machine Intelligence. Link Code

Zhang, R., Meng, Q., & Ma, Z.M. (2024). Deciphering and integrating invariants for neural operator learning with various physical mechanisms. National Science Review. Link Code

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