Xilinx, Inc.

Alireza Khodamoradi

Kornelis Antonius Vissers

Kristof Denolf

Embodiments herein describe a learnable transform block disposed before, or in between, the neural network layers to transform received data into a more computational-friendly domain while preserving discriminative features required for the neural network to generate accurate results. In one embodiment, during a training phase, an AI system learns parameters for the transform block that are then used during the inference phase to transform received data into the computational-friendly domain that has a reduced size input. The transformed data may require less compute resources or less memory usage to process by the underlying hardware device that hosts the neural network.

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San Diego, CA, United States of America

Alireza Khodamoradi