Mountain View, CA, United States of America

Ian Goodfellow

This inventor holds 14 USPTO granted patents and 1 published patent application and 4 EPO patents. Top assignees: Google Inc., Deepmind Technologies Limited, Gdm Holding LLC. Active years: 2015-2026.

USPTO Granted Patents = 14 (Patent Applications = 1)

% Patents Active = 85.7

EPO Patents = 4 (Patent Applications = 2)

Average Co-Inventor Count = 2.8

ph-index = 4

Forward Citations = 77(Granted Patents)

Location History:

Montreal, CA (2015 - 2016)
Brisbane, CA (US) (2020)
Mountain View, CA (US) (2019 - 2024)

Company Filing History:

Deepmind Technologies Limited

where one patent can have more than one assignee

Years Active: 2015-2026

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14 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12738282 - Verifying the provenance of a digital object using watermarking and embeddings (2026-09-15),

2. 12738281 - Verifying the provenance of a digital object using watermarking and embeddings (2026-09-15),

3. 12094474 - Verifying the provenance of a digital object using watermarking and embeddings (2024-09-17),

4. 11869170 - Generating super-resolution images using neural networks (2024-01-09),

5. 11790233 - Generating larger neural networks (2023-10-17),

6. 11651218 - Adversartail training of neural networks (2023-05-16),

7. 11514313 - Sampling from a generator neural network using a discriminator neural network (2022-11-29),

8. 11416745 - Adversarial training of neural networks (2022-08-16),

9. 11354574 - Increasing security of neural networks by discretizing neural network inputs (2022-06-07),

10. 11173599 - Machine learning methods and apparatus related to predicting motion(s) of object(s) in a robot's environment based on image(s) capturing the object(s) and based on parameter(s) for future robot movement in the environment (2021-11-16),

11. 10699191 - Generating larger neural networks (2020-06-30),

12. 10521718 - Adversarial training of neural networks (2019-12-31),

13. 9454714 - Sequence transcription with deep neural networks (2016-09-27),

14. 8965112 - Sequence transcription with deep neural networks (2015-02-24),

Title: Ian Goodfellow: A Pioneer in Neural Networks and Digital Provenance

Introduction

Ian Goodfellow is a prominent inventor known for his groundbreaking work in the field of artificial intelligence and neural networks. He is based in Mountain View, CA (US) and holds a total of 14 patents. His contributions have significantly advanced the capabilities of machine learning and image processing technologies.

Latest Patents

Goodfellow's latest patents include innovative methods for verifying the provenance of digital objects using watermarking and embeddings. This patent outlines systems and apparatus, including computer programs encoded on computer storage media, for verifying the authenticity of digital objects generated by neural networks, such as images or audio. The techniques described are designed to efficiently utilize computing resources while being robust against potential attacks. Another notable patent focuses on generating super-resolution images using neural networks. This involves training a neural network to process images and produce high-quality super-resolution outputs, enhancing the visual fidelity of digital content.

Career Highlights

Throughout his career, Ian Goodfellow has worked with leading technology companies, including Google Inc. and DeepMind Technologies Limited. His work has been instrumental in pushing the boundaries of what is possible with artificial intelligence, particularly in the areas of image generation and verification.

Collaborations

Goodfellow has collaborated with notable figures in the field, including Christian Szegedy and Julian Ibarz. These partnerships have fostered innovation and have led to significant advancements in neural network research.

Conclusion

Ian Goodfellow's contributions to the field of artificial intelligence and neural networks have made him a key figure in modern technology. His patents and collaborations continue to influence the development of advanced machine learning techniques.