22 citations · 44 across the 14 of their papers we have counts for
14 papers
InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks
Yufei Guo, Yuanpei Chen, Liwen Zhang +5
The Spiking Neural Network (SNN) has attracted more and more attention recently. It adopts binary spike signals to transmit information. Benefitting from the information passing pa…
Membrane Potential Batch Normalization for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Yuanpei Chen +5
As one of the energy-efficient alternatives of conventional neural networks (CNNs), spiking neural networks (SNNs) have gained more and more interest recently. To train the deep mo…
RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks
Yufei Guo, Xiaode Liu, Yuanpei Chen +5
Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently. It can significantly reduce energy consumption since they quantize the r…
Learning Multilingual Sentence Representations with Cross-lingual Consistency Regularization
Pengzhi Gao, Liwen Zhang, Zhongjun He +2
Multilingual sentence representations are the foundation for similarity-based bitext mining, which is crucial for scaling multilingual neural machine translation (NMT) system to mo…
Improving Zero-shot Multilingual Neural Machine Translation by Leveraging Cross-lingual Consistency Regularization
Pengzhi Gao, Liwen Zhang, Zhongjun He +2
The multilingual neural machine translation (NMT) model has a promising capability of zero-shot translation, where it could directly translate between language pairs unseen during…
Joint A-SNN: Joint Training of Artificial and Spiking Neural Networks via Self-Distillation and Weight Factorization
Yufei Guo, Weihang Peng, Yuanpei Chen +4
Emerged as a biology-inspired method, Spiking Neural Networks (SNNs) mimic the spiking nature of brain neurons and have received lots of research attention. SNNs deal with binary s…
Real Spike: Learning Real-valued Spikes for Spiking Neural Networks
Yufei Guo, Liwen Zhang, Yuanpei Chen +5
Brain-inspired spiking neural networks (SNNs) have recently drawn more and more attention due to their event-driven and energy-efficient characteristics. The integration of storage…
Scene Clustering Based Pseudo-labeling Strategy for Multi-modal Aerial View Object Classification
Jun Yu, Hao Chang, Keda Lu +3
Multi-modal aerial view object classification (MAVOC) in Automatic target recognition (ATR), although an important and challenging problem, has been under studied. This paper first…
Ultra High Dimensional Change Point Detection
Xin Liu, Liwen Zhang, Zhen Zhang
Structural breaks have been commonly seen in applications. Specifically for detection of change points in time, research gap still remains on the setting in ultra high dimension, w…
Adversarial Attack and Defense of Structured Prediction Models
Wenjuan Han, Liwen Zhang, Yong Jiang +1
Building an effective adversarial attacker and elaborating on countermeasures for adversarial attacks for natural language processing (NLP) have attracted a lot of research in rece…
Latent Variable Sentiment Grammar
Liwen Zhang, Kewei Tu, Yue Zhang
Neural models have been investigated for sentiment classification over constituent trees. They learn phrase composition automatically by encoding tree structures but do not explici…
Acoustic scene classification using multi-layer temporal pooling based on convolutional neural network
Liwen Zhang, Jiqing Han
The performance of an Acoustic Scene Classification (ASC) system is highly depending on the latent temporal dynamics of the audio signal. In this paper, we proposed a multiple laye…
Unidirectional zero reflection as gauged parity-time symmetry
James Gear, Yong Sun, Shiyi Xiao +5
We introduce here the concept of establishing Parity-time symmetry through a gauge transformation involving a shift of the mirror plane for the Parity operation. The corresponding…
Jointly Learning Multiple Measures of Similarities from Triplet Comparisons
Liwen Zhang, Subhransu Maji, Ryota Tomioka
Similarity between objects is multi-faceted and it can be easier for human annotators to measure it when the focus is on a specific aspect. We consider the problem of mapping objec…