surrogate-gradient

The comprehensive bilingual (EN/中文) hub for Spiking Neural Networks — 340+ papers, models, neuromorphic hardware, datasets, tools & research groups.

Minimal PyTorch examples for the four-stage structural evolution from ANN to event-driven SNN: Stage 0 (baseline ANN) → Stage 1 (binarization) → Stage 2 (temporal expansion) → Stage 3 (temporal accumulation) → Stage 4 (reset & sparsity control).

A spiking model of macaque MT and LIP that learns perceptual decisions with surrogate gradients and dopamine-modulated STDP, with an interactive 3D brain.

Brian2-compatible spiking neural network simulation and native training with a Rust engine, CPU/GPU/browser/MPI backends, AtlasIR, and experimental neuromorphic model conversion.

Official code for "Attacking the Spike: On the Security of Spiking Neural Networks to Adversarial Examples" (Neurocomputing 2025). Implements the MDSE adversarial attack for SNNs, CNNs, and Vision Transformers.

The whole male Drosophila CNS connectome (166,700 neurons) used uncut as the spiking core of a language model. Scope, numbers, honest controls, pipeline animation.

Reproducibility code and revision artifacts for neuron heterogeneity, input representation, and dynamical stability in spiking networks.

Device-to-algorithm neuromorphic: train spiking neural nets in snnTorch, then deploy on a simulated memristor crossbar with measured SnS2 device non-idealities.