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What is Probabilistiic Neural Network about?
This paper introduces two novel approximation methods, distribution approximation and clusters approximation, within the framework of probabilistic abstract interpretation for neural network analysis. These methods aim to analyze the density distribution flow of all possible inputs to ensure the robustness and safety of neural networks under probabilistic conditions. The authors illustrate the theoretical workings of these methods and their corresponding abstract transformers through simple examples.
- Author
- Chaitanya Reddy Pulim
- Language
- EN