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Found 3 papers, 2 papers with code
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
In this paper, we show that the smoothness of the estimators, and not the dimension, is the key: benign overfitting is possible if and only if the estimator's derivatives are large enough.
Pitfalls of Climate Network Construction: A Statistical Perspective
Network-based analyses of dynamical systems have become increasingly popular in climate science.
Statistical analysis of Wasserstein GANs with applications to time series forecasting
We provide statistical theory for conditional and unconditional Wasserstein generative adversarial networks (WGANs) in the framework of dependent observations.
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