This repository is the implementation of the paper: ViT2 - Pre-training Vision Transformers for Visual Times Series Forecasting. ViT2 is a framework designed to address generalization & transfer learning limitations of Time-Series-based forecasting models by encoding the time-series to images using GAF and a modified ViT architecture.
python
deep-neural-networks
computer-vision
tensorflow
pytorch
resnet
convolutional-neural-networks
darts
time-series-forecasting
image-encoding
vision-transformer
nbeats
timm
temporal-fusion-transformer
nhits
multi-quantile-regression
gramian-angular-fields
probalistic-forecasting
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Updated
Apr 8, 2024 - Jupyter Notebook