Horw, Switzerland

Gerhard Röthlin

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Disney Enterprises, Inc.. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Gerhard Röthlin. Retrieved from https://idiyas.com/inventor/gerhard-rothlin

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 11.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Gerhard Röthlin: Innovator in Adaptive Sampling Using Deep Learning

Introduction

Gerhard Röthlin is a notable inventor based in Horw, Switzerland. He has made significant contributions to the field of rendering technology, particularly through his innovative patent related to adaptive sampling using deep learning.

Latest Patents

Gerhard Röthlin holds a patent for "Adaptive sampling using deep learning." This patent outlines techniques for adaptive sampling in rendering pipelines. The process involves receiving a plurality of rendered pixel data at a sampler, which includes a first machine learning model. The invention generates a sampling map for the rendering pipeline by predicting pixel values based on a distribution of pixel values. Ultimately, it enables the rendering of images using the sampler, the sampling map, and a denoiser.

Career Highlights

Gerhard Röthlin is currently associated with Disney Enterprises, Inc., where he applies his expertise in deep learning and rendering technologies. His work has contributed to advancements in how images are rendered, enhancing the efficiency and quality of visual outputs.

Collaborations

Some of Gerhard's notable coworkers include Marios Papas and Henrik D Dahlberg. Their collaboration has likely fostered an environment of innovation and creativity within their projects.

Conclusion

Gerhard Röthlin's contributions to adaptive sampling and deep learning represent a significant advancement in rendering technology. His work continues to influence the field and showcases the importance of innovation in enhancing visual experiences.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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