EricZhang1412/Spatial-temporal-ERF
Official repo for NeurIPS 2025 poster: Unveiling the Spatial-temporal Effective Receptive Fields of Spiking Neural Networks
This project helps researchers in neuromorphic computing understand how Spiking Neural Networks (SNNs) process information over space and time. It takes trained SNN models and calculates their 'effective receptive fields,' which reveal what parts of the input an SNN layer truly focuses on. The output helps machine learning researchers and neuroscientists analyze and interpret SNN behavior, especially for visual tasks.
Use this if you are a researcher or engineer working with Spiking Neural Networks and need to analyze their internal mechanisms for visual processing, such as in detection or segmentation.
Not ideal if you are looking for a tool to build or train SNNs from scratch, or if your focus is on traditional deep learning models.
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Python
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Last pushed
Jan 18, 2026
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