Kuan-Chieh Wang

1.5k citations
15 papers · 311 indexed · h-index 7
Topics
Generative Adversarial Networks and Image Synthesis (3 papers)Adversarial Robustness in Machine Learning (3 papers)Anomaly Detection Techniques and Applications (3 papers)

In The Last Decade

Kuan-Chieh Wang

14 papers receiving 293 citations

Peers

Kuan-Chieh Wang
Comparison fields: 5 of 63
  • Artificial Intelligence 160
  • Computer Vision and Pattern Recognition 131
  • Signal Processing 62
  • Automotive Engineering 48
  • Electrical and Electronic Engineering 36
Replace Denghui Zhang with:
Denghui Zhang China
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Citations per field
00.5×10×20×32×
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Citations per year

Countries citing papers authored by Kuan-Chieh Wang

Since Specialization
Citations

This map shows the geographic impact of Kuan-Chieh Wang'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 Kuan-Chieh Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuan-Chieh Wang more than expected).

Fields of papers citing papers by Kuan-Chieh Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuan-Chieh Wang. 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 Kuan-Chieh Wang. The network helps show where Kuan-Chieh Wang may publish in the future.

Co-authorship network of co-authors of Kuan-Chieh Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Kuan-Chieh Wang. A scholar is included among the top collaborators of Kuan-Chieh Wang 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 Kuan-Chieh Wang. Kuan-Chieh Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 0
2 38
3 40
4 9
5 4
6
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
3
7
Cutting out the Middle-Man: Training and Evaluating Energy-Based Models without Sampling
1
8
On the Invertibility of Invertible Neural Networks
1
9
Out-of-distribution Detection in Few-shot Classification
2
10 68
11 30
12
Adversarial Distillation of Bayesian Neural Network Posteriors
3
13
Neural Relational Inference for Interacting Systems
92
14
Dualing GANs
5
15 15

About Kuan-Chieh Wang

Kuan-Chieh Wang is a scholar working on Computer Vision and Pattern Recognition, Instrumentation and Artificial Intelligence, having authored 15 papers that have together received 311 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (131 citations), Signal Processing (62 citations) and Artificial Intelligence (160 citations). Kuan-Chieh Wang has collaborated with scholars based in Canada, Taiwan and United States. Frequent co-authors include Richard S. Zemel, Ethan Fetaya, Thomas Kipf, Max Welling, Serena Yeung, Jixuan Wang, Marc T. Law, Frank Rudzicz, Michael Brudno and Orr Zohar. Their work appears in journals such as ACS Applied Materials & Interfaces, IEEE Transactions on Circuits and Systems for Video Technology and Materials Today Energy.

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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