Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity
Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks
A biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity
NormAD - Normalized Approximate Descent based supervised learning rule for spiking neurons
Circuits for bistable spike-timing-dependent plasticity neuromorphic VLSI synapses
Combining STDP and Reward-Modulated STDP in Deep Convolutional Spiking Neural Networks for Digit Recognition.
A CMOS Spiking Neural Network Circuit with Symmetric/Asymmetric STDP Function
Implementing Synaptic Plasticity in a VLSI Spiking Neural Network Model
Approximate computing for spiking neural networks
Gradient Descent for Spiking Neural Networks
A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity
Spike-Based Synaptic Plasticity in Silicon: Design, Implementation, Application, and Challenges
Training spiking neural networks to associate spatio-temporal input-output spike patterns
Towards a Biologically Plausible Backprop
Spike-Based Compared to Rate-Based Hebbian Learning
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks
Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks
Spiking neural networks , an introduction
STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing
Backpropagation of Hebbian plasticity for lifelong learning.
BackPropagation Through Time
Cloud radio access network (C-RAN): a primer
Deep Metric Learning for Visual Tracking
color image segmentation using k - means clustering and otsu ’ s adaptive thresholding .
Stochastic Simulation of Benign Avascular Tumour growth using the Potts Model.
Deep Spiking Networks