Towards Scalable and Versatile Weight Space Learning
Published in International Conference on Machine Learning, 2024
In this paper, we propose methods to scale weight space learning approaches to large models of varying architectures.
Recommended citation: Schürholt et al., 2024. "Towards Scalable and Versatile Weight Space Learning." ICML 2024. https://arxiv.org/abs/2406.09997