Yanhong Wu

Title: Yanhong Wu: Innovator in Graph Representation Learning

Introduction

Yanhong Wu is a prominent inventor based in San Francisco, CA, known for his contributions to the field of graph representation learning. With a total of 4 patents, he has made significant strides in developing innovative methods that enhance data analysis and machine learning.

Latest Patents

One of Yanhong Wu's latest patents is titled "Dynamic graph representation learning via attention networks." This method involves extracting multiple first datasets from various graph snapshots using a structural self-attention module. The analysis computer then extracts at least a second dataset from these first datasets using a temporal self-attention module across the graph snapshots. This innovative approach allows for effective graph context prediction utilizing the second dataset. Another notable patent is "System, method, and computer program product for determining adversarial examples." This patent describes systems that utilize processors to identify adversarial examples by determining additional inputs based on their proximity to initial inputs, generating vector embeddings, and assessing whether the first input is adversarial based on the concatenated version of these embeddings.

Career Highlights

Yanhong Wu is currently employed at Visa International Service Association, where he applies his expertise in machine learning and data analysis. His work focuses on developing advanced systems that improve the security and efficiency of financial transactions.

Collaborations

Yanhong has collaborated with notable colleagues, including Hao Yang and Yuhang Wu, who contribute to his innovative projects and research endeavors.

Conclusion

Yanhong Wu's work in graph representation learning and adversarial example detection showcases his commitment to advancing technology in meaningful ways. His contributions continue to influence the fields of data analysis and machine learning, making him a significant figure in innovation.