BNS: Building Network Structures Dynamically for Continual Learning

48 citations recorded by the source corpus.

How researchers see this paper

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CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One (2022, neutral): “At the same time, we consider the SOTA methods that improve continual learning in terms of architecture, such as BNS [34] and MARK [17].”
Adaptive Orthogonal Projection for Batch and Online Continual Learning (2022, background): “Many other papers use related approaches (Zenke, Poole, and Ganguli 2017; Fernando et al. 2017; Aljundi et al. 2017; Ritter, Botev, and Barber 2018; Xu and Zhu 2018; Kemker and Kanan 2018; Parisi et al. 2018; Ahn et al. 2019; Hu et al. 2021; Dhar et al. 2019; Adel, Zhao, and Turner 2020).”
Divide and not forget: Ensemble of selectively trained experts in Continual Learning (2024, methodology): “We compare SEED to: HAT (Serr`a et al., 2018), MARK (Hurtado et al., 2021), and BNS (Qin et al., 2021).”
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition (2022, methodology): “While the approach of Mendez and Eaton (2021) sidesteps forgetting in the structure over modules by making it task-specific, the controller of Qin et al. (2021) is susceptible to catastrophic forgetting.”