Average Co-Inventor Count = 5.1

ph-index = 5

Forward Citations = 73(Granted Patents)

Location History:

Zurich, CH (2020)
Zürich, CH (2019 - 2022)

Company Filing History:

14 out of 2,767

Disney Enterprises, Inc.

Eth Zurich (eidgenossische Technische Hochschule Zurich)

Disnev Enterprises, Inc.

patent

where one patent can have more than one assignee

Years Active: 2019-2024

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15 patents (USPTO):Sort by Forward Citations

Abstract keywords

1. 12169914 - Temporal techniques of denoising Monte Carlo renderings using neural networks (2024-12-17),

2. 11532073 - Temporal techniques of denoising Monte Carlo renderings using neural networks (2022-12-20),

3. 11037274 - Denoising Monte Carlo renderings using progressive neural networks (2021-06-15),

4. 10818080 - Piecewise-polynomial coupling layers for warp-predicting neural networks (2020-10-27),

5. 10796414 - Kernel-predicting convolutional neural networks for denoising (2020-10-06),

6. 10789686 - Denoising Monte Carlo renderings using machine learning with importance sampling (2020-09-29),

7. 10706508 - Adaptive sampling in Monte Carlo renderings using error-predicting neural networks (2020-07-07),

8. 10699382 - Denoising Monte Carlo renderings using neural networks with asymmetric loss (2020-06-30),

9. 10672109 - Multi-scale architecture of denoising monte carlo renderings using neural networks (2020-06-02),

10. 10621695 - Video super-resolution using an artificial neural network (2020-04-14),

11. 10607319 - Denoising monte carlo renderings using progressive neural networks (2020-03-31),

12. 10586310 - Denoising Monte Carlo renderings using generative adversarial neural networks (2020-03-10),

13. 10572979 - Denoising Monte Carlo renderings using machine learning with importance sampling (2020-02-25),

14. 10491856 - Video frame interpolation using a convolutional neural network (2019-11-26),

15. 10475165 - Kernel-predicting convolutional neural networks for denoising (2019-11-12),

Title: Innovations of Brian McWilliams: A Pioneer in Denoising Techniques

Introduction

Brian McWilliams is a notable inventor based in Zurich, Switzerland. With an impressive portfolio of 15 patents, McWilliams has significantly contributed to the field of neural networks and rendering technologies. His innovative approaches to denoising Monte Carlo renderings highlight his expertise and forward-thinking mindset.

Latest Patents

Among McWilliams' latest contributions is the patent titled "Temporal Techniques of Denoising Monte Carlo Renderings Using Neural Networks." This invention features a modular architecture designed specifically for denoising Monte Carlo renderings through the application of neural networks. The temporal approach he proposes extracts and combines feature representations from neighboring frames instead of relying solely on recurrent connections for building temporal context. His multiscale architecture includes distinct single-frame or temporal denoising modules tailored for various scales, alongside one or more scale compositor neural networks that adaptively blend these individual scales. Additionally, an error-predicting module aids in generating adaptive sampling maps for renderers, ensuring a more uniform distribution of residual noise. The use of an asymmetric loss function during training of the neural networks further allows for control over the variance-bias trade-off during the denoising process.

Career Highlights

Throughout his career, McWilliams has been affiliated with prominent companies, including Disney Enterprises, Inc. and Pixar. His tenure at these renowned organizations has solidified his standing as a leading inventor in the animation and rendering industries, showcasing his exceptional talent in integrating innovation within creative environments.

Collaborations

McWilliams has worked alongside talented coworkers such as Thijs Vogels and Fabrice Rousselle. These collaborations have enabled him to enhance his inventions and push the boundaries of what is possible in the realm of neural networks and rendering technologies.

Conclusion

Brian McWilliams continues to be a significant influence in the field of innovation with his groundbreaking patents and collaborations. His dedication to advancing rendering techniques, particularly through the integration of neural networks, exemplifies the spirit of invention. As technology continues to evolve, McWilliams' contributions will surely play a vital role in shaping the future of digital rendering.

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