- We wrote a benchmark paper with many practical insights on (the benefits of) active learning for training neural PDE solvers. 🚀 I was happy to be a co-advisor on this project - most of the credit goes to Daniel and Marimuthu.
- Neural surrogates can accelerate PDE solving but need expensive ground-truth training data. Can we reduce the training data size with active learning (AL)? In our NeurIPS D3S3 poster, we introduce AL4PDE, an extensible AL benchmark for autoregressive neural PDE solvers. 🧵
