| Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels P Chen, B Liao, G Chen, S Zhang International Conference on Machine Learning (ICML), 2019, 2019 | 394 | 2019 |
| Ultrafast multi-focus 3-D nano-fabrication based on two-photon polymerization Q Geng, D Wang, P Chen, SC Chen Nature communications 10 (1), 2179, 2019 | 313 | 2019 |
| Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise P Chen, J Ye, G Chen, J Zhao, PA Heng Proceedings of the AAAI Conference on Artificial Intelligence, 2021 | 111 | 2021 |
| Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks G Chen, P Chen, Y Shi, CY Hsieh, B Liao, S Zhang arXiv preprint arXiv:1905.05928, 2019 | 91 | 2019 |
| Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models G Chen, P Chen, CY Hsieh, CK Lee, B Liao, R Liao, W Liu, J Qiu, Q Sun, ... Workshop of International Conference on Learning Representations (ICLR …, 2019 | 71 | 2019 |
| Log Hyperbolic Cosine Loss Improves Variational Auto-Encoder P Chen, G Chen, S Zhang | 43 | 2018 |
| Deep learning-enabled orbital angular momentum-based information encryption transmission F Feng, J Hu, Z Guo, JA Gan, PF Chen, G Chen, C Min, X Yuan, ... ACS Photonics 9 (3), 820-829, 2022 | 39 | 2022 |
| Noise against noise: stochastic label noise helps combat inherent label noise P Chen, G Chen, J Ye, PA Heng International Conference on Learning Representations. (ICLR 2021, spotlight), 2020 | 36 | 2020 |
| Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels P Chen, J Ye, G Chen, J Zhao, PA Heng Proceedings of the AAAI Conference on Artificial Intelligence, 2021 | 33 | 2021 |
| Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training C Xue, L Yu, P Chen, Q Dou, PA Heng IEEE Transactions on Medical Imaging 41 (6), 1371-1382, 2022 | 32 | 2022 |
| Acknowledging the unknown for multi-label learning with single positive labels D Zhou, P Chen, Q Wang, G Chen, PA Heng European Conference on Computer Vision, 423-440, 2022 | 24 | 2022 |
| Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization P Chen, W Liu, CY Hsieh, G Chen, S Zhang arXiv preprint arXiv:1906.05488, 2019 | 17 | 2019 |
| Improving Graph Representation Learning by Contrastive Regularization K Ma, H Yang, H Yang, T Jin, P Chen, Y Chen, BF Kamhoua, J Cheng arXiv preprint arXiv:2101.11525, 2021 | 13 | 2021 |
| Data transmission with up to 100 orbital angular momentum modes via commercial multi-mode fiber and parallel neural networks F Feng, JA Gan, J Nong, PF Chen, G Chen, C Min, X Yuan, M Somekh Optics Express 30 (13), 23149-23162, 2022 | 11 | 2022 |
| Apparatus and method for laser beam shaping and scanning S Chen, G Qiang, D Wang, P Chen, D Zhang US Patent 10,884,250, 2021 | 11 | 2021 |
| AI-assisted spectrometer based on multi-mode optical fiber speckle patterns F Feng, J Gan, PF Chen, W Lin, GY Chen, C Min, X Yuan, M Somekh Optics Communications 522, 128675, 2022 | 8 | 2022 |
| A Meta Approach to Defend Noisy Labels by the Manifold Regularizer PSDR P Chen, B Liao, G Chen, S Zhang arXiv preprint arXiv:1906.05509, 2019 | 5 | 2019 |
| Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction H Tang, J Hao, G Chen, P Chen, Z Meng, Y Yang, L Wang arXiv preprint arXiv:1905.11100, 2019 | 4 | 2019 |
| How convolutional-neural-network detects optical vortex scattering fields J Hu, Z Guo, Y Fu, JA Gan, PF Chen, G Chen, C Min, X Yuan, F Feng Optics and Lasers in Engineering 160, 107246, 2023 | 3 | 2023 |
| Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction H Tang, Z Meng, G Chen, P Chen, C Chen, Y Yang, L Zhang, W Liu, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9834-9842, 2021 | 2 | 2021 |
Shengyu Zhang（张胜誉）TencentVerified email at cse.cuhk.edu.hk
