Google Machine Learning Temporal Residual Connections Patent

The European Patent Office granted Google patent EP4232959A1 covering machine learning models featuring temporal residual connections for improved sequential data processing. The patent, filed by inventors Liangzhe Yuan and Yongzhe, includes claims related to neural network architectures with temporal skip connections and covers G06N classifications for deep learning models.

Technology companies and AI developers working on sequential data processing, time-series analysis, or temporal modeling should review the patent claims to assess potential licensing needs or infringement risks. Patent grants establish enforceable intellectual property rights within designated EPO member states, potentially affecting product development in machine learning, natural language processing, and time-series prediction applications.