Domain bias caused by individual differences and device variations severely limits BCI's practical application, while existing methods struggle with ...

(A) Overall structure of the model. MLP, multilayer perceptron. (B) Structure of the time encoder module. (C) Structure of the channel encoder module. BN, batch normalization. “Domain bias caused by ...

Abstract: In this letter, we propose a hyperparameter optimization method for adaptive filtering based on deep unrolling, termed the deep unrolling affine projection (DAP) algorithm. The core idea is ...

Unconventional reservoirs, including shale gas, tight oil, and coalbed methane formations, have emerged as vital contributors to global energy security, accounting for a substantial portion of the ...

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This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

I’m fitting a recurrent SLDS (rSLDS) to simultaneous ensemble spiking from two brain areas. The dataset is large (200+ neurons, ~90 min per session), so even after binning the (neurons × time) sample ...

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...