Tzu-Kuo Huang
About
In The Last Decade
Tzu-Kuo Huang
10 papers receiving 863 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Automotive Engineering 349
- Artificial Intelligence 313
- Computer Vision and Pattern Recognition 280
- Information Systems 269
- Building and Construction 141
Countries citing papers authored by Tzu-Kuo Huang
This map shows the geographic impact of Tzu-Kuo Huang'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 Tzu-Kuo Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tzu-Kuo Huang more than expected).
Fields of papers citing papers by Tzu-Kuo Huang
This network shows the impact of papers produced by Tzu-Kuo Huang. 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 Tzu-Kuo Huang. The network helps show where Tzu-Kuo Huang may publish in the future.
Co-authorship network of co-authors of Tzu-Kuo Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Tzu-Kuo Huang. A scholar is included among the top collaborators of Tzu-Kuo Huang 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 Tzu-Kuo Huang. Tzu-Kuo Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps | Tzu-Kuo Huang, Nemanja Djuric et al. | 8 | |
| 2 | Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks breakdown → | Henggang Cui, Vladan Radosavljević et al. | 414 | |
| 3 | Active search and bandits on graphs using sigma-optimality | Uncertainty in Artificial Intelligence | Yifei Ma, Tzu-Kuo Huang et al. | 14 |
| 4 | Active Transfer Learning under Model Shift | International Conference on Machine Learning | Xuezhi Wang, Tzu-Kuo Huang et al. | 30 |
| 5 | Spectral Learning of Hidden Markov Models from Dynamic and Static Data | International Conference on Machine Learning | Tzu-Kuo Huang, Jeff Schneider | 1 |
| 6 | Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition | Neural Information Processing Systems | Tzu-Kuo Huang, Jeff Schneider | 1 |
| 7 | Learning Auto-regressive Models from Sequence and Non-sequence Data | Neural Information Processing Systems | Tzu-Kuo Huang, Jeff Schneider | 8 |
| 8 | Learning Nonlinear Dynamic Models from Non-sequenced Data | International Conference on Artificial Intelligence and Statistics | Tzu-Kuo Huang, Le Song et al. | 3 |
| 9 | Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization breakdown → | Figshare | Liang Xiong, Xi Chen et al. | 410 |
| 10 | Learning linear dynamical systems without sequence information | Tzu-Kuo Huang, Jeff Schneider | 4 |
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.