Wenxuan Pan

most citedIP

^{2}

-RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks

1 citations · 1 across the 3 of their papers we have counts for

collaborators

Showing cs.NEShow all

1 paper · 1 filter

cs.NE2025★ 1 cited

IP $^{2}$ -RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks

Yingchao Yu, Yaochu Jin, Kuangrong Hao +5

Learning-to-learn (L2L), defined as progressively faster learning across similar tasks, is fundamental to both neuroscience and artificial intelligence. However, its neural basis r…

IP2-RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks

IP $^{2}$ -RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks