Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Chao Zhang

Chao Zhang

Training Algorithm Matters for the Performance of Neural Network Potential


Sep 08, 2021
Yunqi Shao, Florian M. Dietrich, Carl Nettelblad, Chao Zhang

Figure 1 for Training Algorithm Matters for the Performance of Neural Network Potential
Figure 2 for Training Algorithm Matters for the Performance of Neural Network Potential
Figure 3 for Training Algorithm Matters for the Performance of Neural Network Potential
Figure 4 for Training Algorithm Matters for the Performance of Neural Network Potential

  Access Paper or Ask Questions

IEEE BigData 2021 Cup: Soft Sensing at Scale


Sep 07, 2021
Sergei Petrov, Chao Zhang, Jaswanth Yella, Yu Huang, Xiaoye Qian, Sthitie Bom

Figure 1 for IEEE BigData 2021 Cup: Soft Sensing at Scale
Figure 2 for IEEE BigData 2021 Cup: Soft Sensing at Scale
Figure 3 for IEEE BigData 2021 Cup: Soft Sensing at Scale
Figure 4 for IEEE BigData 2021 Cup: Soft Sensing at Scale
* 4 pages, 4 figures, for IEEE Big Data Cup challenge 2021 
  Access Paper or Ask Questions

Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition


Sep 03, 2021
Guangzhi Sun, Chao Zhang, Philip C. Woodland

Figure 1 for Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition
Figure 2 for Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition
Figure 3 for Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition
Figure 4 for Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition
* Submitted to ASRU 2021 
  Access Paper or Ask Questions

Auto-encoder based Model for High-dimensional Imbalanced Industrial Data


Aug 05, 2021
Chao Zhang, Sthitie Bom

Figure 1 for Auto-encoder based Model for High-dimensional Imbalanced Industrial Data
Figure 2 for Auto-encoder based Model for High-dimensional Imbalanced Industrial Data
Figure 3 for Auto-encoder based Model for High-dimensional Imbalanced Industrial Data
Figure 4 for Auto-encoder based Model for High-dimensional Imbalanced Industrial Data
* 12 pages, 7 figures and 5 tables, submitted to ICONIP 2021 
  Access Paper or Ask Questions

Towards Making Deep Learning-based Vulnerability Detectors Robust


Aug 04, 2021
Zhen Li, Jing Tang, Deqing Zou, Qian Chen, Shouhuai Xu, Chao Zhang, Yichen Li, Hai Jin

Figure 1 for Towards Making Deep Learning-based Vulnerability Detectors Robust
Figure 2 for Towards Making Deep Learning-based Vulnerability Detectors Robust
Figure 3 for Towards Making Deep Learning-based Vulnerability Detectors Robust
Figure 4 for Towards Making Deep Learning-based Vulnerability Detectors Robust

  Access Paper or Ask Questions

Adapting GPT, GPT-2 and BERT Language Models for Speech Recognition


Jul 29, 2021
Xianrui Zheng, Chao Zhang, Philip C. Woodland

Figure 1 for Adapting GPT, GPT-2 and BERT Language Models for Speech Recognition
Figure 2 for Adapting GPT, GPT-2 and BERT Language Models for Speech Recognition
Figure 3 for Adapting GPT, GPT-2 and BERT Language Models for Speech Recognition
Figure 4 for Adapting GPT, GPT-2 and BERT Language Models for Speech Recognition

  Access Paper or Ask Questions

Efficient Vision Transformers via Fine-Grained Manifold Distillation


Jul 06, 2021
Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, Dacheng Tao

Figure 1 for Efficient Vision Transformers via Fine-Grained Manifold Distillation
Figure 2 for Efficient Vision Transformers via Fine-Grained Manifold Distillation
Figure 3 for Efficient Vision Transformers via Fine-Grained Manifold Distillation
Figure 4 for Efficient Vision Transformers via Fine-Grained Manifold Distillation

  Access Paper or Ask Questions

STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis


Jul 04, 2021
Chao Zhang, Wenqiang Yi, Yuanwei Liu, Zhiguo Ding, Lingyang Song

Figure 1 for STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis
Figure 2 for STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis
Figure 3 for STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis
Figure 4 for STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis

  Access Paper or Ask Questions

Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition


Jul 01, 2021
Qiujia Li, Chao Zhang, Philip C. Woodland

Figure 1 for Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition
Figure 2 for Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition
Figure 3 for Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition
Figure 4 for Combining Frame-Synchronous and Label-Synchronous Systems for Speech Recognition
* Submitted to IEEE/ACM Transactions on Audio Speech and Language Processing 
  Access Paper or Ask Questions

MFR 2021: Masked Face Recognition Competition


Jun 29, 2021
Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal, Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Ε truc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso

Figure 1 for MFR 2021: Masked Face Recognition Competition
Figure 2 for MFR 2021: Masked Face Recognition Competition
Figure 3 for MFR 2021: Masked Face Recognition Competition
Figure 4 for MFR 2021: Masked Face Recognition Competition
* Accepted at International Join Conference on Biometrics (IJCB 2021) 
  Access Paper or Ask Questions

GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins


Jun 24, 2021
Lixue Liu, Chao Zhang, Dacheng Tao

Figure 1 for GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins
Figure 2 for GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins
Figure 3 for GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins
Figure 4 for GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins

  Access Paper or Ask Questions

Image Deformation Estimation via Multi-Objective Optimization


Jun 08, 2021
Takumi Nakane, Xuequan Lu, Haoran Xie, Chao Zhang

Figure 1 for Image Deformation Estimation via Multi-Objective Optimization
Figure 2 for Image Deformation Estimation via Multi-Objective Optimization
Figure 3 for Image Deformation Estimation via Multi-Objective Optimization
Figure 4 for Image Deformation Estimation via Multi-Objective Optimization

  Access Paper or Ask Questions

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting


Jun 07, 2021
Harshavardhan Kamarthi, Lingkai Kong, Alexander RodrΓ­guez, Chao Zhang, B. Aditya Prakash

Figure 1 for When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Figure 2 for When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Figure 3 for When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Figure 4 for When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
* 16 pages, 12 Figures 
  Access Paper or Ask Questions

Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling


Jun 02, 2021
Chao Zhang, Samson Lasaulce, Martin Hennebel, Lucas Saludjian, Patrick Panciatici, H. Vincent Poor

Figure 1 for Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling
Figure 2 for Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling
Figure 3 for Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling
Figure 4 for Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling
* Applied Energy, 297:117106, 2021 
 * Published in Applied Energy 
  Access Paper or Ask Questions

BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition


May 30, 2021
Yinghao Li, Pranav Shetty, Lucas Liu, Chao Zhang, Le Song

Figure 1 for BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
Figure 2 for BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
Figure 3 for BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
Figure 4 for BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition

  Access Paper or Ask Questions

A Federated Learning Framework for Nonconvex-PL Minimax Problems


May 29, 2021
Jiahao Xie, Chao Zhang, Yunsong Zhang, Zebang Shen, Hui Qian

Figure 1 for A Federated Learning Framework for Nonconvex-PL Minimax Problems
Figure 2 for A Federated Learning Framework for Nonconvex-PL Minimax Problems
Figure 3 for A Federated Learning Framework for Nonconvex-PL Minimax Problems
Figure 4 for A Federated Learning Framework for Nonconvex-PL Minimax Problems

  Access Paper or Ask Questions

PanGu-$Ξ±$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation


Apr 26, 2021
Wei Zeng, Xiaozhe Ren, Teng Su, Hui Wang, Yi Liao, Zhiwei Wang, Xin Jiang, ZhenZhang Yang, Kaisheng Wang, Xiaoda Zhang, Chen Li, Ziyan Gong, Yifan Yao, Xinjing Huang, Jun Wang, Jianfeng Yu, Qi Guo, Yue Yu, Yan Zhang, Jin Wang, Hengtao Tao, Dasen Yan, Zexuan Yi, Fang Peng, Fangqing Jiang, Han Zhang, Lingfeng Deng, Yehong Zhang, Zhe Lin, Chao Zhang, Shaojie Zhang, Mingyue Guo, Shanzhi Gu, Gaojun Fan, Yaowei Wang, Xuefeng Jin, Qun Liu, Yonghong Tian

Figure 1 for PanGu-$Ξ±$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
Figure 2 for PanGu-$Ξ±$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
Figure 3 for PanGu-$Ξ±$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
Figure 4 for PanGu-$Ξ±$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
* The technique report for PanGu-$\alpha$ 
  Access Paper or Ask Questions

Sketch-based Normal Map Generation with Geometric Sampling


Apr 23, 2021
Yi He, Haoran Xie, Chao Zhang, Xi Yang, Kazunori Miyata

* accepted in International Workshop on Advanced Image Technology 2021, 5 pages, 2 figures 
  Access Paper or Ask Questions

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning


Apr 23, 2021
Sheldon Fung, Xuequan Lu, Chao Zhang, Chang-Tsun Li

Figure 1 for DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning
Figure 2 for DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning
Figure 3 for DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning
Figure 4 for DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning
* accepted to IJCNN2021 
  Access Paper or Ask Questions

Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods


Apr 12, 2021
Xianjie Gao, Xueguan Song, Maolin Shi, Chao Zhang, Hongwei Zhang

Figure 1 for Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
Figure 2 for Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
Figure 3 for Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
Figure 4 for Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods

  Access Paper or Ask Questions

A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds


Apr 09, 2021
Chao Zhang, Xiaojun Chen, Shiqian Ma

Figure 1 for A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds
Figure 2 for A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds
Figure 3 for A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds
Figure 4 for A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds

  Access Paper or Ask Questions

Semantic Scene Completion via Integrating Instances and Scene in-the-Loop


Apr 08, 2021
Yingjie Cai, Xuesong Chen, Chao Zhang, Kwan-Yee Lin, Xiaogang Wang, Hongsheng Li

Figure 1 for Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
Figure 2 for Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
Figure 3 for Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
Figure 4 for Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
* CVPR 2021 
  Access Paper or Ask Questions

A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training


Mar 12, 2021
Adnan Haider, Chao Zhang, Florian L. Kreyssig, Philip C. Woodland

Figure 1 for A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training
Figure 2 for A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training
Figure 3 for A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training
Figure 4 for A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training

  Access Paper or Ask Questions

Using Cognitive Models to Train Warm Start Reinforcement Learning Agents for Human-Computer Interactions


Mar 10, 2021
Chao Zhang, Shihan Wang, Henk Aarts, Mehdi Dastani

Figure 1 for Using Cognitive Models to Train Warm Start Reinforcement Learning Agents for Human-Computer Interactions

  Access Paper or Ask Questions

Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning


Jan 21, 2021
Lang Huang, Chao Zhang, Hongyang Zhang

Figure 1 for Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning
Figure 2 for Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning
Figure 3 for Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning
Figure 4 for Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning
* Journal version of arXiv:2002.10319 [cs.LG] (NeurIPS2020). 19 pages, 15 figures, 11 tables 
  Access Paper or Ask Questions

Hybrid Quantum-Classical Graph Convolutional Network


Jan 15, 2021
Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang, Haiwang Yu, Shinjae Yoo

Figure 1 for Hybrid Quantum-Classical Graph Convolutional Network
Figure 2 for Hybrid Quantum-Classical Graph Convolutional Network
Figure 3 for Hybrid Quantum-Classical Graph Convolutional Network
Figure 4 for Hybrid Quantum-Classical Graph Convolutional Network

  Access Paper or Ask Questions

Theory-based Habit Modeling for Enhancing Behavior Prediction


Jan 05, 2021
Chao Zhang, Joaquin Vanschoren, Arlette van Wissen, Daniel Lakens, Boris de Ruyter, Wijnand A. IJsselsteijn

Figure 1 for Theory-based Habit Modeling for Enhancing Behavior Prediction
Figure 2 for Theory-based Habit Modeling for Enhancing Behavior Prediction
Figure 3 for Theory-based Habit Modeling for Enhancing Behavior Prediction
Figure 4 for Theory-based Habit Modeling for Enhancing Behavior Prediction

  Access Paper or Ask Questions

Quantum Convolutional Neural Networks for High Energy Physics Data Analysis


Dec 22, 2020
Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang, Haiwang Yu, Shinjae Yoo

Figure 1 for Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
Figure 2 for Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
Figure 3 for Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
Figure 4 for Quantum Convolutional Neural Networks for High Energy Physics Data Analysis

  Access Paper or Ask Questions

Partial Gromov-Wasserstein Learning for Partial Graph Matching


Dec 09, 2020
Weijie Liu, Chao Zhang, Jiahao Xie, Zebang Shen, Hui Qian, Nenggan Zheng


  Access Paper or Ask Questions

SAR-Net: A End-to-End Deep Speech Accent Recognition Network


Dec 08, 2020
Wei Wang, Chao Zhang, Xiaopei Wu

Figure 1 for SAR-Net: A End-to-End Deep Speech Accent Recognition Network
Figure 2 for SAR-Net: A End-to-End Deep Speech Accent Recognition Network
Figure 3 for SAR-Net: A End-to-End Deep Speech Accent Recognition Network
Figure 4 for SAR-Net: A End-to-End Deep Speech Accent Recognition Network
* 10 pages, 7 figures, journal 
  Access Paper or Ask Questions