Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization

ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing

(2019) Gopalakrishnan Srinivasan et al.   Frontiers in Neuroscience

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

(2019) Abhronil Sengupta et al.   Frontiers in Neuroscience

Towards artificial general intelligence with hybrid Tianjic chip architecture

(2019) Jing Pei et al.   NATURE

Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks

(2019) Emre O. Neftci et al.   IEEE SIGNAL PROCESSING MAGAZINE

Towards spike-based machine intelligence with neuromorphic computing

(2019) Kaushik Roy et al.   NATURE

STDP-based spiking deep convolutional neural networks for object recognition

(2018) Saeed Reza Kheradpisheh et al.   NEURAL NETWORKS

ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural Networks

(2018) Priyadarshini Panda et al.   IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Deep Spiking Convolutional Neural Network Trained with Unsupervised Spike Timing Dependent Plasticity

(2018) Chankyu Lee et al.   IEEE Transactions on Cognitive and Developmental Systems

Training Deep Spiking Convolutional Neural Networks With STDP-Based Unsupervised Pre-training Followed by Supervised Fine-Tuning

(2018) Chankyu Lee et al.   Frontiers in Neuroscience

STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing

(2018) Gopalakrishnan Srinivasan et al.   ACM Journal on Emerging Technologies in Computing Systems

Deep Learning With Spiking Neurons: Opportunities and Challenges

(2018) Michael Pfeiffer et al.   Frontiers in Neuroscience

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

(2017) Yoeri van de Burgt et al.   NATURE MATERIALS

Supervised Learning Based on Temporal Coding in Spiking Neural Networks

(2017) Hesham Mostafa   IEEE Transactions on Neural Networks and Learning Systems

Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

(2017) Abhronil Sengupta et al.   Applied Physics Reviews

Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

(2016) Zhongrui Wang et al.   NATURE MATERIALS

Training Deep Spiking Neural Networks Using Backpropagation

(2016) Jun Haeng Lee et al.   Frontiers in Neuroscience

Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

(2016) Abhronil Sengupta et al.   Physical Review Applied

Deep learning

(2015) Yann LeCun et al.   NATURE

Unsupervised learning of digit recognition using spike-timing-dependent plasticity

(2015) Peter U. Diehl et al.   Frontiers in Computational Neuroscience

Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition

(2014) Yongqiang Cao et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Real-time classification and sensor fusion with a spiking deep belief network

(2013) Peter O'Connor et al.   Frontiers in Neuroscience

Competitive STDP-Based Spike Pattern Learning

(2009) Timothée Masquelier et al.   NEURAL COMPUTATION