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For the Inventor, By the Inventor

London, United Kingdom

Wojciech Czarnecki

USPTO Granted Patents = 12 

 

Average Co-Inventor Count = 4.2

ph-index = 2

Forward Citations = 34(Granted Patents)


Company Filing History:

goldMedal12 out of 308 
 
Deepmind Technologies Limited
 patents

Years Active: 2020-2025

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12 patents (USPTO):Explore Patents
1. 12314856 - Population based training of neural networks (2025-05-27),
2. 12020164 - Neural networks for scalable continual learning in domains with sequentially learned tasks (2024-06-25),
3. 11983634 - Multi-task neural network systems with task-specific policies and a shared policy (2024-05-14),
4. 11941527 - Population based training of neural networks (2024-03-26),
5. 11842281 - Reinforcement learning with auxiliary tasks (2023-12-12),
6. 11842261 - Deep reinforcement learning with fast updating recurrent neural networks and slow updating recurrent neural networks (2023-12-12),
7. 11715009 - Training neural networks using synthetic gradients (2023-08-01),
8. 11604985 - Population based training of neural networks (2023-03-14),
9. 11132609 - Multi-task neural network systems with task-specific policies and a shared policy (2021-09-28),
10. 11113605 - Reinforcement learning using agent curricula (2021-09-07),
11. 10956820 - Reinforcement learning with auxiliary tasks (2021-03-23),
12. 10872293 - Deep reinforcement learning with fast updating recurrent neural networks and slow updating recurrent neural networks (2020-12-22),

Title: Wojciech Czarnecki: Innovator in Neural Network Technologies

Introduction

Wojciech Czarnecki is a prominent inventor based in London, GB, known for his significant contributions to the field of neural networks. With a total of 12 patents to his name, he has been at the forefront of developing innovative methods and systems that enhance machine learning capabilities.

Latest Patents

Czarnecki's latest patents include groundbreaking work on "Population based training of neural networks." This patent outlines methods, systems, and apparatus for training neural networks using an iterative process that optimizes network parameters and hyperparameters. Another notable patent is focused on "Neural networks for scalable continual learning in domains with sequentially learned tasks." This invention addresses the challenges of training neural networks on new tasks while retaining knowledge from previous tasks, showcasing his commitment to advancing machine learning technologies.

Career Highlights

Czarnecki is currently employed at DeepMind Technologies Limited, a leading company in artificial intelligence research. His work at DeepMind has positioned him as a key player in the development of advanced neural network methodologies. His innovative approaches have not only contributed to the company's success but have also influenced the broader field of artificial intelligence.

Collaborations

Throughout his career, Czarnecki has collaborated with notable colleagues, including Maxwell Elliot Jaderberg and Razvan Pascanu. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Wojciech Czarnecki's contributions to neural network technologies exemplify his innovative spirit and dedication to advancing the field of artificial intelligence. His patents and work at DeepMind continue to shape the future of machine learning, making him a significant figure in the industry.

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