Fei Tian
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Statistical and Nonlinear Physics top 5%
- Mechanics of Materials top 10%
- Information Systems top 5%
- Topics
- Natural Language Processing Techniques (16 papers)Topic Modeling (15 papers)Hydrocarbon exploration and reservoir analysis (14 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Fei Tian
66 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 964
- Computer Vision and Pattern Recognition 562
- Statistical and Nonlinear Physics 206
- Mechanics of Materials 188
- Information Systems 136
Countries citing papers authored by Fei Tian
This map shows the geographic impact of Fei Tian'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 Fei Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Tian more than expected).
Fields of papers citing papers by Fei Tian
This network shows the impact of papers produced by Fei Tian. 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 Fei Tian. The network helps show where Fei Tian may publish in the future.
Co-authorship network of co-authors of Fei Tian
This figure shows the co-authorship network connecting the top 25 collaborators of Fei Tian. A scholar is included among the top collaborators of Fei Tian 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 Fei Tian. Fei Tian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 14 | |
| 4 | 3 | |
| 5 | 19 | |
| 6 | 13 | |
| 7 | 82 | |
| 8 | Towards Binary-Valued Gates for Robust LSTM Training | 2 |
| 9 | Adversarial Neural Machine Translation | 35 |
| 10 | Learning to Teach with Dynamic Loss Functions | 16 |
| 11 | Learning to Teach. | 9 |
| 12 | 80 | |
| 13 | Identification of fracture-vug complex from karsted carbonates and its significance in petroleum geology | 2 |
| 14 | Deliberation Networks: Sequence Generation Beyond One-Pass Decoding | 117 |
| 15 | 105 | |
| 16 | Word embedding revisited: a new representation learning and explicit matrix factorization perspective | 54 |
| 17 | A Probabilistic Model for Learning Multi-Prototype Word Embeddings | 68 |
| 18 | Fault Accommodation Zones and Their Controling Effects on Hydrocarbon Distribution in Yong 8 Fault Block,Dongying Sag | 1 |
| 19 | Development and Application of Materials Database of Finite Element Simulation Software Deform | 3 |
| 20 | Turbulence analysis and experiments of low-specific-speed centrifugal pump. | 5 |
About Fei Tian
Fei Tian is a scholar working on Geology, Artificial Intelligence and Leadership and Management, having authored 69 papers that have together received 1.8k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Topic Modeling (15 papers) and Hydrocarbon exploration and reservoir analysis (14 papers). The work is most often cited by research in Artificial Intelligence (964 citations), Computer Vision and Pattern Recognition (562 citations) and Statistical and Nonlinear Physics (206 citations). Fei Tian has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Tie‐Yan Liu, Enhong Chen, Bin Gao, Qing Cui, Tao Qin, Lijun Wu, Tie‐Yan Liu, Yingce Xia, Yi-Ren Wang and Jianhuang Lai. Their work appears in journals such as Scientific Reports, Carbon and Earth-Science Reviews.
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.