Pengfei Chen

According to our database, Pengfei Chen authored at least 11 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Acknowledging the Unknown for Multi-label Learning with Single Positive Labels.

Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng

Proceedings of the Computer Vision, 2022

2021

Noise against noise: stochastic label noise helps combat inherent label noise.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction.

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

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

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

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

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models.

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

CoRR, 2019

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

Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang

CoRR, 2019

Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization.

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

CoRR, 2019

Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction.

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

CoRR, 2019

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

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

CoRR, 2019

Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels.

Pengfei Chen, Benben Liao, Guangyong Chen, Shengyu Zhang

Proceedings of the 36th International Conference on Machine Learning, 2019