Priyadarshini Panda

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

Chankyu Lee, Syed Shakib Sarwar, Priyadarshini Panda et al. · Frontiers in Neuroscience · 2020 · 418 citations · Full text

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

Chankyu Lee, Priyadarshini Panda, Gopalakrishnan Srinivasan et al. · Frontiers in Neuroscience · 2018 · 199 citations · Full text

Engineering, Machine Learning, Neural Networks (Machine Learning) +21

Domain Adaptation Without Source Data

Youngeun Kim, Donghyeon Cho, Kyeongtak Han et al. · IEEE Transactions on Artificial Intelligence · 2021 · 171 citations

Engineering, Machine Learning, Natural Language Processing +16

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike\n Timing Dependent Backpropagation

Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda et al. · arXiv (Cornell University) · 2020 · 164 citations · Full text

Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks From Scratch

Youngeun Kim, Priyadarshini Panda · Frontiers in Neuroscience · 2021 · 153 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +16