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Found 4 papers, 1 papers with code
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
However, far less attention has been paid to the overfitting problem of models in recommendation systems, which, on the contrary, is recognized as a critical issue for deep neural networks.
LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values
Multivariate time series (MTS) prediction is ubiquitous in real-world fields, but MTS data often contains missing values.
PDGM: a Neural Network Approach to Solve Path-Dependent Partial Differential Equations
In this paper, we propose a novel numerical method for Path-Dependent Partial Differential Equations (PPDEs).
Bifurcation Spiking Neural Network
Inspired by this insight, by enabling the spike generation function to have adaptable eigenvalues rather than parametric control rates, we develop the Bifurcation Spiking Neural Network (BSNN), which has an adaptive firing rate and is insensitive to the setting of control rates.
