The research delves into the challenge of sample-based inference (SBI) for Bayesian neural networks (BNNs) due to the size and structure of the network’s parameter space. The authors propose that…
Continue readingThe article studies the impact of overparameterization on the complexity and sensitivity of the function represented by neural networks. It discusses the ‘double-descent’ phenomenon, where highly overparameterized models escape overfitting…
Continue readingThe paper presents an in-depth analysis of the joint effect of task similarity and overparameterization on catastrophic forgetting in continual learning. The researchers focus on two-task continual linear regression, where…
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