Few-shot evaluation and a per-shot plasticity metric show that meta-learning short sequences of future tasks in continual image classification induces learning-to-learn behavior.
Online con- tinual learning: A systematic literature review of approaches, challenges, and benchmarks
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CLP-SNN matches replay-based accuracy rehearsal-free on OpenLORIS few-shot continual learning and achieves 113x lower latency plus 6600x lower energy on Loihi 2 than edge-GPU baselines through algorithmic efficiency and neuromorphic hardware co-design.
A validation-gated multi-agent framework enables online adaptation of thermal-hydraulic surrogates and reduces forecast error by 19% under regime shifts on experimental loop data.
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Online Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network
CLP-SNN matches replay-based accuracy rehearsal-free on OpenLORIS few-shot continual learning and achieves 113x lower latency plus 6600x lower energy on Loihi 2 than edge-GPU baselines through algorithmic efficiency and neuromorphic hardware co-design.