ISI-CV derives a synaptic importance score from the regularity of neuron firing intervals to enable continual learning without gradients or forgetting on SNNs.
Theilman and James B
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.
citing papers explorer
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Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization
ISI-CV derives a synaptic importance score from the regularity of neuron firing intervals to enable continual learning without gradients or forgetting on SNNs.
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Post-Moore Technologies for Plasma Simulation: A Community Roadmap
No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.