DER++
PulseAugur coverage of DER++ — every cluster mentioning DER++ across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New framework analyzes bias vs. class correspondence in incremental learning
This research paper introduces a new framework to analyze the effectiveness of logit replay methods in class-incremental learning. The proposed method distinguishes between correctable bias and class correspondence, eva…
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New framework ReDIL-GNN tackles domain shift in circuit GNNs
Researchers have introduced ReDIL-GNN, a novel framework designed to address domain shift in circuit graph neural networks (GNNs) that arises from logic resynthesis. This framework enables GNNs to adapt to new synthesis…
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New research reframes continual learning beyond forgetting and plasticity · 5 sources tracked
Recent research explores new facets of continual learning, moving beyond traditional challenges like catastrophic forgetting and plasticity loss. One paper introduces "data co-observation" as a distinct factor, demonstr…