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1 Neural ODE

#Deep Learning #Neural ODE

The concepts and ideas of neural ODE

4 Neyman-Pearson Theory

#Statistics #Basics #Hypothesis Testing

The Neyman-Pearson hypothesis testing tests two hypothesis, hypothesis $H$, and an alternative …

Autoregressive Denoising Diffusion Model

#Diffusion Model

TimeGrad

MTGNN

#graph neural network #graph #forecasting #time series

Key Components Time Convolution (TC) Module Time Convolution The temporal convolution is responsible …

MTGNN

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Multivariate Time Series Forecasting with Graph Neural Networks

Pytorch Data Parallelism

#PyTorch #Parallel

Data parallelism in pytorch

CUDA Memory

#CUDA

Optimizing memory operations for CUDA

Empirical Correlation Coefficient (CORR)

#Time Series #Forecasting

The Empirical Correlation Coefficient (CORR) is an evaluation metric in time series forecasting,1 $$ …

Root Relative Squared Error (RSE)

#Time Series #Forecasting

The Root Relative Squared Error (RSE) is an evaluation metric in time series forecasting,1 $$ …

Dilated Convolution

#Convolution

For a convolution $$ f*h(x) = \sum_{s+t=x} f(s) h(t), $$ the dilated version of it is1 $$ f*_l h(x) …

Over-Smoothing in Graph Neural Networks

#graph #graph neural networks #GNN

Over-smoothing is the problem that the representations on each node of the graph neural networks …

Multiple Comparison Problem

#Statistics #Hypothesis Testing

In a multiple comparisons problem, we deal with multiple statistical tests simultaneously. Examples …