Yee Whye Teh

Title: Innovations of Yee Whye Teh

Introduction

Yee Whye Teh is a prominent inventor based in Oxford, GB. He has made significant contributions to the fields of machine learning and computer vision. With a total of 4 patents, his work focuses on advancing technology through innovative methods and systems.

Latest Patents

One of his latest patents is titled "Object discovery in images through categorizing object parts." This patent involves methods, systems, and apparatus for detecting objects in images, including computer programs encoded on computer storage media. The process includes obtaining an input image and generating predicted part feature data, which helps identify objects depicted in the image. Another notable patent is "Neural networks for scalable continual learning in domains with sequentially learned tasks." This invention outlines methods for scalable continual learning using neural networks, focusing on training active and knowledge subnetworks on new machine learning tasks.

Career Highlights

Yee Whye Teh has worked with notable companies such as DeepMind Technologies Limited and Google Inc. His experience in these leading technology firms has allowed him to contribute to groundbreaking advancements in artificial intelligence and machine learning.

Collaborations

Throughout his career, Yee Whye Teh has collaborated with talented individuals, including Razvan Pascanu and Raia Thais Hadsell. Their joint efforts have further propelled innovations in their respective fields.

Conclusion

Yee Whye Teh's contributions to technology through his patents and collaborations highlight his role as a leading inventor in the realm of machine learning and computer vision. His work continues to influence advancements in these critical areas.