Zurich, Switzerland

Bodo Rueckauer


Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Bodo Rueckauer: Innovator in Neural Network Technology

Introduction

Bodo Rueckauer is a prominent inventor based in Zurich, Switzerland. He has made significant contributions to the field of neural networks, particularly through his innovative patent that enhances the efficiency of processing input samples.

Latest Patents

Bodo Rueckauer holds a patent titled "Method and apparatus with neural network layer contraction." This processor-implemented neural network method involves determining a reference sample among sequential input samples to be processed by a neural network. The neural network comprises an input layer, one or more hidden layers, and an output layer. The method includes performing an inference process to obtain an output activation of the output layer based on operations in the hidden layers corresponding to the reference sample input to the input layer. Additionally, it determines layer contraction parameters for establishing an affine transformation relationship between the input layer and the output layer, facilitating the approximation of the inference process. The method also allows for inference on other sequential input samples using the affine transformation based on the determined layer contraction parameters.

Career Highlights

Bodo Rueckauer has worked with notable organizations, including Samsung Electronics Co., Ltd. and the University of Zurich. His experience in these institutions has contributed to his expertise in neural network technologies and their applications.

Collaborations

Throughout his career, Bodo has collaborated with esteemed colleagues such as Shih-Chii Liu and Tobi Delbruck. These collaborations have further enriched his work and innovations in the field.

Conclusion

Bodo Rueckauer is a distinguished inventor whose work in neural network technology has paved the way for advancements in processing input samples. His contributions continue to influence the field and inspire future innovations.

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