Search Results for author: Ruiyuan Gao

Found 8 papers, 3 papers with code

Out-of-Distribution Detection with Semantic Mismatch under Masking

1 code implementation31 Jul 2022 Yijun Yang, Ruiyuan Gao, Qiang Xu

This paper proposes a novel out-of-distribution (OOD) detection framework named MoodCat for image classifiers.

OOD Detection Out-of-Distribution Detection

DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation

1 code implementation16 Mar 2022 Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, Qiang Xu

This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation, named DeciWatch.

3D Human Pose Estimation 3D Pose Estimation +1

T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis

no code implementations ICLR 2022 Minhao Liu, Ailing Zeng, Qiuxia Lai, Ruiyuan Gao, Min Li, Jing Qin, Qiang Xu

In this work, we propose a novel tree-structured wavelet neural network for time series signal analysis, namely T-WaveNet, by taking advantage of an inherent property of various types of signals, known as the dominant frequency range.

Activity Recognition Representation Learning +1

Relational Graph Neural Network Design via Progressive Neural Architecture Search

no code implementations30 May 2021 Ailing Zeng, Minhao Liu, Zhiwei Liu, Ruiyuan Gao, Jing Qin, Qiang Xu

We propose a novel solution to addressing a long-standing dilemma in the representation learning of graph neural networks (GNNs): how to effectively capture and represent useful information embedded in long-distance nodes to improve the performance of nodes with low homophily without leading to performance degradation in nodes with high homophily.

Neural Architecture Search Node Classification +1

ModuleNet: Knowledge-inherited Neural Architecture Search

no code implementations10 Apr 2020 Yaran Chen, Ruiyuan Gao, Fenggang Liu, Dongbin Zhao

Unlike previous search algorithms, and benefiting from inherited knowledge, our method is able to directly search for architectures in the macro space by NSGA-II algorithm without tuning parameters in these \textit{module}s. Experiments show that our strategy can efficiently evaluate the performance of new architecture even without tuning weights in convolutional layers.

Neural Architecture Search

Privacy for Rescue: A New Testimony Why Privacy is Vulnerable In Deep Models

no code implementations31 Dec 2019 Ruiyuan Gao, Ming Dun, Hailong Yang, Zhongzhi Luan, Depei Qian

Existing research works rely on metrics that are either impractical or insufficient to measure the effectiveness of privacy protection methods in the above scenario, especially from the aspect of a single user.

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