Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A general analysis of the limiting distribution of neural network functions is performed, with emphasis on non-Gaussian limits.  show that with i.i.d. symmetric stable output ights, and more generally with ights distributed from the normal domain of attraction of a stable variable, that the neural functions converge in distribution to stable processes. Conditions are also investigated under which Gaussian limits do occur when the ights are independent but not identically distributed. Some particularly tractable classes of stable distributions are examined, and the possibility of learning with such processes.
['Ricky Der', 'Daniel D. Lee']
I am writing a research paper on a idea Beyond Gaussian Processes: On the Distributions of Infinite Networks
[{"from": "human", "value": "I am writing a research paper on a idea Beyond Gaussian Processes: On the Distributions of Infinite Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A general analysis of the limiting distribution of neural network functions is performed, with emphasis on non-Gaussian limits.  show that with i.i.d. symmetric stable output ights, and more generally with ights distributed from the normal domain of attraction of a stable variable, that the neural functions converge in distribution to stable processes. Conditions are also investigated under which Gaussian limits do occur when the ights are independent but not identically distributed. Some particularly tractable classes of stable distributions are examined, and the possibility of learning with such processes."}]