Beijing, China

Yiwen Guo

Average Co-Inventor Count = 6.5

ph-index = 3

Forward Citations = 22(Granted Patents)

Forward Citations (Not Self Cited) = 9(Sep 21, 2024)


Years Active: 2021-2025

where 'Filed Patents' based on already Granted Patents

19 patents (USPTO):

Title: Innovations of Yiwen Guo in Deep Learning

Introduction

Yiwen Guo is a prominent inventor based in Beijing, China, known for his contributions to deep learning technologies and neural networks. With an impressive portfolio of 19 patents, he has significantly advanced the methodologies employed in artificial intelligence.

Latest Patents

Among his latest inventions, Yiwen Guo has worked on Methods and systems for budgeted and simplified training of deep neural networks. This patent focuses on training deep neural networks (DNNs) efficiently by utilizing training sub-images from down-sampled training images. The system employs a recurrent deep Q-network (RDQN) featuring a local attention mechanism, enhancing performance by applying both hard and soft attention on generated feature maps. Another notable patent is Dynamic neural network surgery, which discusses techniques for compressing pre-trained dense deep neural networks into sparsely connected variants to optimize their implementation. These innovations exemplify his commitment to enhancing the efficiency and effectiveness of deep learning systems.

Career Highlights

Yiwen Guo is currently a leading innovator at Intel Corporation, where he applies his expertise in neural networks and deep learning. His role involves researching and developing advanced technologies that impact various applications within the tech industry. Through his position at Intel, he continues to push the boundaries of what is possible in artificial intelligence.

Collaborations

Collaboration is key in the field of innovation, and Yiwen Guo has worked alongside talented individuals such as Anbang Yao and Yurong Chen. Their collective efforts have contributed to the development of groundbreaking technologies in deep learning and artificial intelligence.

Conclusion

Yiwen Guos work exemplifies the transformative nature of innovation in the field of deep learning. His contributions, particularly in the areas of efficient training of neural networks and dynamic optimization techniques, are paving the way for future advancements in artificial intelligence. As technology continues to evolve, inventors like Yiwen Guo play a crucial role in shaping the landscape of innovation.

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