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Slax: A Composable JAX Library for Rapid and Flexible Prototyping of
  Spiking Neural Networks

Slax: A Composable JAX Library for Rapid and Flexible Prototyping of Spiking Neural Networks

8 April 2024
Thomas M. Summe
Siddharth Joshi
ArXivPDFHTML

Papers citing "Slax: A Composable JAX Library for Rapid and Flexible Prototyping of Spiking Neural Networks"

4 / 4 papers shown
Title
A Truly Sparse and General Implementation of Gradient-Based Synaptic Plasticity
A Truly Sparse and General Implementation of Gradient-Based Synaptic Plasticity
Jamie Lohoff
Anil Kaya
Florian Assmuth
Emre Neftci
40
0
0
20 Jan 2025
Online Training Through Time for Spiking Neural Networks
Online Training Through Time for Spiking Neural Networks
Mingqing Xiao
Qingyan Meng
Zongpeng Zhang
D.K. He
Zhouchen Lin
32
59
0
09 Oct 2022
EXODUS: Stable and Efficient Training of Spiking Neural Networks
EXODUS: Stable and Efficient Training of Spiking Neural Networks
F. Bauer
Gregor Lenz
Saeid Haghighatshoar
Sadique Sheik
BDL
26
15
0
20 May 2022
Training Feedback Spiking Neural Networks by Implicit Differentiation on
  the Equilibrium State
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State
Mingqing Xiao
Qingyan Meng
Zongpeng Zhang
Yisen Wang
Zhouchen Lin
98
59
0
29 Sep 2021
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