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Quantitative CLTs in Deep Neural Networks
We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$.
Berry-Esseen bounds of second moment estimators for Gaussian processes observed at high frequency
Let $Z:=\{Z_t, t\geq0\}$ be a stationary Gaussian process.
Gaussian Processes
Statistics Theory
Probability
Statistics Theory
