3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 3 cited
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong +8
We give extensive empirical evidence against the common belief that variational learning is ineffective for large neural networks. We show that an optimizer called Improved Variati…
cs.LG2023★ 1 cited
The Memory Perturbation Equation: Understanding Model's Sensitivity to Data
Peter Nickl, Lu Xu, Dharmesh Tailor +2
Understanding model's sensitivity to its training data is crucial but can also be challenging and costly, especially during training. To simplify such issues, we present the Memory…