Open Neural Network Exchange

Open Neural Network Exchange (ONNX) is an open standard for representing machine learning models, aiming to improve interoperability between different deep learning frameworks and hardware platforms. Current research focuses on enhancing ONNX's capabilities for model optimization techniques like pruning and quantization, as well as improving explainability through methods such as Shapley values. This facilitates easier deployment of models across diverse environments, boosting efficiency and accessibility for researchers and developers in various fields, including high-performance computing and embedded systems. Addressing challenges like conversion errors and ensuring semantic correctness remain key areas of ongoing investigation.