F
Feng Chen
Researcher at Tsinghua University
Publications - 6
Citations - 932
Feng Chen is an academic researcher from Tsinghua University. The author has contributed to research in topics: Neuromorphic engineering & Deep learning. The author has an hindex of 5, co-authored 6 publications receiving 506 citations.
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Journal ArticleDOI
Towards artificial general intelligence with hybrid Tianjic chip architecture.
Jing Pei,Lei Deng,Sen Song,Sen Song,Mingguo Zhao,Youhui Zhang,Shuang Wu,Guanrui Wang,Zhe Zou,Zhenzhi Wu,Wei He,Feng Chen,Ning Deng,Si Wu,Yu Wang,Yujie Wu,Z. Yang,Cheng Ma,Guoqi Li,Wentao Han,Huanglong Li,Huaqiang Wu,Rong Zhao,Yuan Xie,Luping Shi +24 more
TL;DR: The Tianjic chip is presented, which integrates neuroscience-oriented and computer-science-oriented approaches to artificial general intelligence to provide a hybrid, synergistic platform and is expected to stimulate AGI development by paving the way to more generalized hardware platforms.
Proceedings Article
Training and Inference with Integers in Deep Neural Networks
TL;DR: Wang et al. as discussed by the authors developed a new method termed as "WAGE" to discretize both training and inference, where weights, activations, gradients, and errors among layers are shifted and linearly constrained to low-bitwidth integers.
Posted Content
Training and Inference with Integers in Deep Neural Networks
TL;DR: Empirically, this work demonstrates the potential to deploy training in hardware systems such as integer-based deep learning accelerators and neuromorphic chips with comparable accuracy and higher energy efficiency, which is crucial to future AI applications in variable scenarios with transfer and continual learning demands.
Proceedings ArticleDOI
Development of a neuromorphic computing system
Luping Shi,Jing Pei,Ning Deng,Dong Wang,Lei Deng,Yu Wang,Youhui Zhang,Feng Chen,Mingguo Zhao,Sen Song,Fei Zeng,Guoqi Li,Huanglong Li,Cheng Ma +13 more
TL;DR: A new design rule for developing a brain inspired computing system based on some recent findings in brain science is proposed and a neuromorphic chip, named `Tianji' chip is designed and fabricated.
Proceedings Article
Convolution with even-sized kernels and symmetric padding
TL;DR: This work quantifies the shift problem occurs in even-sized kernel convolutions by an information erosion hypothesis, and eliminates it by proposing symmetric padding on four sides of the feature maps (C2sp, C4sp).