Jianxi Gao

Title: Innovations of Jianxi Gao

Introduction

Jianxi Gao is a prominent inventor based in Niskayuna, NY (US). She has made significant contributions to the field of neural networks and machine learning. Her innovative approach has led to the development of a unique patent that enhances the capabilities of neural network models.

Latest Patents

Jianxi Gao holds a patent titled "Neural capacitance: neural network selection via edge dynamics." This invention involves the removal of an output layer from a pre-trained neural network model. A neural capacitance probe unit with multiple layers is incorporated on top of one or more bottom layers of the pre-trained model. The probe unit is randomly initialized, and the modified neural network model is trained by fine-tuning the bottom layers on a target dataset for a maximum number of epochs. The model comprises the neural capacitance probe unit, which is integrated with multiple layers on top of the pre-trained network. An adjacency matrix is obtained from the initialized probe unit, and a neural capacitance metric is computed using this matrix. An active model is then selected based on the neural capacitance metric, allowing for the configuration of a machine learning system using the active model. This innovative approach has the potential to significantly improve the efficiency and effectiveness of neural network applications.

Career Highlights

Throughout her career, Jianxi Gao has worked with notable organizations, including IBM and Rensselaer Polytechnic Institute. Her experience in these institutions has allowed her to refine her skills and contribute to groundbreaking research in the field of artificial intelligence and machine learning.

Collaborations

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Conclusion

Jianxi Gao's contributions to the field of neural networks through her innovative patent demonstrate her expertise and commitment to advancing technology. Her work continues to inspire future developments in machine learning and artificial intelligence.