most citedA Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks

8 citations · 8 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Supervised Learning for Analog and RF Circuit Design: Benchmarks and Comparative Insights

Asal Mehradfar, Xuzhe Zhao, Yue Niu +4

Automating analog and radio-frequency (RF) circuit design using machine learning (ML) significantly reduces the time and effort required for parameter optimization. This study expl…

cs.LG2023★ 8 cited

A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks

Sara Babakniya, Zalan Fabian, Chaoyang He +2

Deep learning models often suffer from forgetting previously learned information when trained on new data. This problem is exacerbated in federated learning (FL), where the data is…