Search Results for author: Xiaowei Li

Found 12 papers, 3 papers with code

Weight-based Channel-model Matrix Framework: a reasonable solution for EEG-based cross-dataset emotion recognition

no code implementations13 Sep 2022 Huayu Chen, Huanhuan He, Shuting Sun, Jianxiu Li, Xuexiao Shao, Junxiang Li, Xiaowei Li, Bin Hu

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results.

EEG Emotion Recognition

Breaking the accuracy and resolution limitation of filter- and frequency-to-time mapping-based time and frequency acquisition methods by broadening the filter bandwidth

no code implementations9 Aug 2022 Pengcheng Zuo, Dong Ma, Xiaowei Li, Yang Chen

In this paper, the filter- and frequency-to-time mapping (FTTM)-based photonics-assisted time and frequency acquisition methods are comprehensively analyzed and the accuracy and resolution limitation in the fast sweep scenario is broken by broadening the filter bandwidth.

Fault-Tolerant Deep Learning: A Hierarchical Perspective

no code implementations5 Apr 2022 Cheng Liu, Zhen Gao, Siting Liu, Xuefei Ning, Huawei Li, Xiaowei Li

With the rapid advancements of deep learning in the past decade, it can be foreseen that deep learning will be continuously deployed in more and more safety-critical applications such as autonomous driving and robotics.

Autonomous Driving

PLUGIn: A simple algorithm for inverting generative models with recovery guarantees

no code implementations NeurIPS 2021 Babhru Joshi, Xiaowei Li, Yaniv Plan, Ozgur Yilmaz

We prove that, when weights are Gaussian and layer widths $n_i \gtrsim 5^i n_0$ (up to log factors), the algorithm converges geometrically to a neighbourhood of $x$ with high probability.

PLUGIn-CS: A simple algorithm for compressive sensing with generative prior

no code implementations NeurIPS Workshop Deep_Invers 2021 Babhru Joshi, Xiaowei Li, Yaniv Plan, Ozgur Yilmaz

After a sufficient number of iterations, the estimation errors for both $x$ and $\mathcal{G}(x)$ are at most in the order of $\sqrt{4^dn_0/m} \|\epsilon\|$.

Compressive Sensing

R2F: A Remote Retraining Framework for AIoT Processors with Computing Errors

no code implementations7 Jul 2021 Dawen Xu, Meng He, Cheng Liu, Ying Wang, Long Cheng, Huawei Li, Xiaowei Li, Kwang-Ting Cheng

It takes the remote AIoT processor with soft errors in the training loop such that the on-site computing errors can be learned with the application data on the server and the retrained models can be resilient to the soft errors.

A study of resting-state EEG biomarkers for depression recognition

no code implementations23 Feb 2020 Shuting Sun, Jianxiu Li, Huayu Chen, Tao Gong, Xiaowei Li, Bin Hu

Results: Functional connectivity feature PLI is superior to the linear features and nonlinear features.

EEG

Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction

1 code implementation CVPR 2020 Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, Xiaowei Li

Inspired by the frequency band decomposition characteristic of Human Vision System (HVS), we propose a video prediction network based on multi-level wavelet analysis to deal with spatial and temporal information in a unified manner.

 Ranked #1 on Video Prediction on KTH (PSNR metric)

Video Generation Video Prediction

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

no code implementations20 Feb 2020 Hanshu Cai, Yiwen Gao, Shuting Sun, Na Li, Fuze Tian, Han Xiao, Jianxiu Li, Zhengwu Yang, Xiaowei Li, Qinglin Zhao, Zhenyu Liu, Zhijun Yao, Minqiang Yang, Hong Peng, Jing Zhu, Xiaowei Zhang, Guoping Gao, Fang Zheng, Rui Li, Zhihua Guo, Rong Ma, Jing Yang, Lan Zhang, Xiping Hu, Yumin Li, Bin Hu

The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications.

EEG

Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications

no code implementations28 Jan 2020 Halyun Jeong, Xiaowei Li, Yaniv Plan, Özgür Yılmaz

In many applications, e. g., compressed sensing, this norm may be large, or even growing with dimension, and thus it is important to characterize this dependence.

See and Think: Disentangling Semantic Scene Completion

1 code implementation NeurIPS 2018 Shice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li

Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.

2D Semantic Segmentation 3D Semantic Scene Completion +1

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