colinshane's repositories
stdp-mnist
Using spiking neurons and spike-timing-dependent plasticity to classify the MNIST handwritten digits.
hands_on_Ml_with_Sklearn_and_TF
OReilly Hands On Machine Learning with Scikit Learn and TensorFlow (Sklearn与TensorFlow机器学习实用指南)
spiketorch
Experiments with spiking neural networks (SNNs) in PyTorch. See https://github.com/Hananel-Hazan/bindsnet for the successor to this project.
190565
Supervised learning in spiking neural networks with FORCE training (Nicola & Clopath 2017)
BabbleNN
Spiking neural network model of canonical babbling development
CARLsim3
CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.
DLCISNN
Cerebellum-inspired spiking neural network(DLCISNN), a hybrid of Spiking Neural Network and Deep learning networks with the architecture and firing behaviour inspired from cerebellar microcircuitry.
helllo-world
it's my first day in github. hello, the whole new world
Neural-Network-Tutorials
Code for my tutorials on Artificial Neural Networks
Neuronz
FYP Project - Neural Networks using STDP
Number_Crunch
University Final Year Project: High-performance computing with SpiNNaker (spiking neural network architecture)
rpg_corner_events
Fast Event-based Corner Detection
S2NN-HLS
Spiking neural network for Zynq devices with Vivado HLS
snn-ml
Spiking Neural Networks for Machine Learning
snn-mnist
spiking neural network
snn-rl
Reinforcement Learning for Spiking Neural Networks
snn_global_pattern_induction
Framework to train and simulate a spiking neural network (SNN) using Brian2, that implements a learning rule that combines STDP with a global feedback mechanism to support strong, contrasty pattern formation.
SNNs-In-Tensorflow
Implementation of a Spiking Neural Network in Tensorflow.
spike-1
Spiking neural network simulator
SPIKE_RCNN
Spike Detection based on Region-based Convolutional Neural Network
Spiking-Neural-Network-Simple-Classifier
this project was my final project of Computational Neural science course in University of Tehran in Computer science department. it's very simple with just one layer of spiking neurons and two neurons that classify the learned objects. it uses Intensity to latency coding model and STDP learning
SpikingConvNet
Building arbitrarily deep models of Spiking Convolutional Neural Networks on SpiNNaker
SpikingMoYF
Spiking Neural Network
SpiNNakerCSPs
This repository will help you create a spiking neural network which structure represents a constraint satisfaction problem and which dynamics implements a stochastic search to solve it.
Training-Neural-Networks-for-Event-Based-End-to-End-Robot-Control
TUM Master’s thesis: Steering a robot with an event-based vision sensor in a lane-keeping task using methods such as Deep Reinforcement Learning or Spiking Neural Networks.