Tong Che

1.3k total citations
9 papers, 268 citations indexed

About

Tong Che is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Tong Che has authored 9 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Tong Che's work include Adversarial Robustness in Machine Learning (5 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Tong Che is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Tong Che collaborates with scholars based in Algeria, Canada and China. Tong Che's co-authors include Yoshua Bengio, Ruixiang Zhang, Zoubin Ghahramani, Yangqiu Song, Xiaofeng Liu, Bo Li, Ziwei Liu, Dongsheng Li, Kaiyang Zhou and Yubin Ge and has published in prestigious journals such as Scientific Reports, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell University).

In The Last Decade

Tong Che

9 papers receiving 263 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tong Che Algeria	7	199	140	42	16	13	9	268
Eden Belouadah France	3	266 1.3×	160 1.1×	33 0.8×	13 0.8×	10 0.8×	5	318
Debasmit Das United Kingdom	7	170 0.9×	135 1.0×	28 0.7×	37 2.3×	12 0.9×	19	303
Qianfen Jiao China	6	312 1.6×	298 2.1×	53 1.3×	17 1.1×	10 0.8×	12	438
Songlin Dong China	9	392 2.0×	232 1.7×	59 1.4×	13 0.8×	5 0.4×	19	482
Xinyuan Chang China	6	332 1.7×	247 1.8×	53 1.3×	16 1.0×	5 0.4×	8	430
Ruoxi Sun China	5	271 1.4×	198 1.4×	31 0.7×	12 0.8×	5 0.4×	8	363
Yucen Luo China	4	269 1.4×	221 1.6×	49 1.2×	12 0.8×	5 0.4×	6	326
Limin Su China	5	226 1.1×	135 1.0×	23 0.5×	6 0.4×	27 2.1×	13	293
Muhammad Uzair Khattak United Arab Emirates	5	287 1.4×	298 2.1×	30 0.7×	19 1.2×	5 0.4×	10	468

Countries citing papers authored by Tong Che

Since Specialization

Citations

This map shows the geographic impact of Tong Che's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tong Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tong Che more than expected).

Fields of papers citing papers by Tong Che

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tong Che. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tong Che. The network helps show where Tong Che may publish in the future.

Co-authorship network of co-authors of Tong Che

This figure shows the co-authorship network connecting the top 25 collaborators of Tong Che. A scholar is included among the top collaborators of Tong Che based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tong Che. Tong Che is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Li, Haichao, Yixuan Ma, Mingrui Duan, Xin Wang, & Tong Che. (2023). Defects detection of GMAW process based on convolutional neural network algorithm. Scientific Reports. 13(1). 21219–21219. 9 indexed citations

2.

Xu, Zhicheng, Hongbing Cheng, Tong Che, et al.. (2023). Secure Collaborative Learning in Mining Pool via Robust and Efficient Verification. 794–805. 6 indexed citations

3.

Che, Tong, Xiaofeng Liu, Site Li, et al.. (2021). Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models. Proceedings of the AAAI Conference on Artificial Intelligence. 35(8). 7002–7010. 18 indexed citations

4.

Li, Bo, et al.. (2021). Energy-Based Open-World Uncertainty Modeling for Confidence Calibration. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9282–9291. 28 indexed citations

5.

Che, Tong, Ruixiang Zhang, Jascha Sohl‐Dickstein, et al.. (2020). Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling. arXiv (Cornell University). 33. 12275–12287. 3 indexed citations

6.

Liu, Xiaofeng, Yang Zou, Tong Che, et al.. (2019). Conservative Wasserstein Training for Pose Estimation. 8261–8271. 24 indexed citations

7.

Zhang, Ruixiang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, & Yangqiu Song. (2018). MetaGAN: an adversarial approach to few-shot learning. Cambridge University Engineering Department Publications Database. 31. 2371–2380. 161 indexed citations

8.

Che, Tong, et al.. (2018). Combining Model-based and Model-free RL via Multi-step Control Variates. 3 indexed citations

9.

Zhang, Saizheng, Yuhuai Wu, Tong Che, et al.. (2016). Architectural Complexity Measures of Recurrent Neural Networks. Neural Information Processing Systems. 29. 1822–1830. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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