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Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction


Mar 03, 2021
Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Zhaopeng Meng

* Accepted paper on AAAI 2021. arXiv admin note: text overlap with arXiv:1905.11100 

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Improving Graph Representation Learning by Contrastive Regularization


Jan 27, 2021
Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng


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Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise


Dec 10, 2020
Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng

* Accepted by AAAI 2021 

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Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels


Dec 08, 2020
Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng

* Accepted by AAAI 2021 

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Integrated Traffic Simulation-Prediction System using Neural Networks with Application to the Los Angeles International Airport Road Network


Aug 05, 2020
Yihang Zhang, Aristotelis-Angelos Papadopoulos, Pengfei Chen, Faisal Alasiri, Tianchen Yuan, Jin Zhou, Petros A. Ioannou

* 19 pages. Under review 

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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models


Jun 22, 2019
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang

* Authors are listed in alphabetical order 

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A Meta Approach to Defend Noisy Labels by the Manifold Regularizer PSDR


Jun 13, 2019
Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang

* Correspondence to: Guangyong Chen  

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Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization


Jun 13, 2019
Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang

* 1. Pengfei Chen and Weiwen Liu have equal contribution. 2. Correspondence to: Guangyong Chen  

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Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction


May 27, 2019
Hongyao Tang, Jianye Hao, Guangyong Chen, Pengfei Chen, Zhaopeng Meng, Yaodong Yang, Li Wang

* 10 pages for paper and 6 pages for the supplementary material 

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Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks


May 15, 2019
Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang

* Correspondence to:Benben Liao  

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Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels


May 13, 2019
Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang

* Correspondence to: Guangyong Chen  

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Understanding Convolution for Semantic Segmentation


Jun 01, 2018
Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, Garrison Cottrell

* WACV 2018. Updated acknowledgements. Source code: https://github.com/TuSimple/TuSimple-DUC 

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