2025
GradMetaNet: An Equivariant Architecture for Learning on Gradients
NeurIPS 2025poster
Gradients of neural networks encode valuable information for optimization, editing, and analysis of models. Therefore, practitioners often treat gradients as inputs to task-specific algorithms, e.g., using gradient statistics for pruning or optimization. Recent works explore *learning* algorithms th…