Search Results for author: Jie Gu

Found 7 papers, 3 papers with code

Interest-oriented Universal User Representation via Contrastive Learning

no code implementations18 Sep 2021 Qinghui Sun, Jie Gu, Bei Yang, Xiaoxiao Xu, Renjun Xu, Shangde Gao, Hong Liu, Huan Xu

Universal user representation has received many interests recently, with which we can be free from the cumbersome work of training a specific model for each downstream application.

Contrastive Learning Representation Learning +1

Elliptic Blowup Equations for 6d SCFTs. IV: Matters

1 code implementation4 Jun 2020 Jie Gu, Babak Haghighat, Albrecht Klemm, Kaiwen Sun, Xin Wang

Given the recent geometrical classification of 6d $(1, 0)$ SCFTs, a major question is how to compute for this large class their elliptic genera.

High Energy Physics - Theory Mathematical Physics Mathematical Physics

Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification

1 code implementation9 Sep 2019 kaisheng Liao, Yaodong Zhao, Jie Gu, Yaping Zhang, Yi Zhong

A representative sequential convolutional recurrent neural network architecture with the two-layer convolutional neural network and subsequent two-layer long short-term memory neural network is developed to suggest the option for fast automatic modulation classification.

Classification Dimensionality Reduction +1

Progressive Sparse Local Attention for Video object detection

no code implementations ICCV 2019 Chaoxu Guo, Bin Fan, Jie Gu, Qian Zhang, Shiming Xiang, Veronique Prinet, Chunhong Pan

Instead of relying on optical flow, this paper proposes a novel module called Progressive Sparse Local Attention (PSLA), which establishes the spatial correspondence between features across frames in a local region with progressively sparser stride and uses the correspondence to propagate features.

Optical Flow Estimation Video Object Detection

Structure-Aware Convolutional Neural Networks

1 code implementation NeurIPS 2018 Jianlong Chang, Jie Gu, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, Chunhong Pan

Convolutional neural networks (CNNs) are inherently subject to invariable filters that can only aggregate local inputs with the same topological structures.

Action Recognition Activity Detection +3

A Random Matrix Theoretical Approach to Early Event Detection in Smart Grid

no code implementations31 Jan 2015 Xing He, Robert Caiming Qiu, Qian Ai, Yinshuang Cao, Jie Gu, Zhijian Jin

With the statistical procedure, the proposed method is universal and fast; moreover, it is robust against traditional EED challenges (such as error accumulations, spurious correlations, and even bad data in core area).

Anomaly Detection Decision Making +1

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