GitHub20d
sunshine-wavelan/Stock-predict-with-Tranformer-LSTM
conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia pip3 install pandas pip3 install matplotlib pip3 install tqdm pip3 install tensorboardX pip3 install opencv-python ...
IEEE19d
Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach
We utilized a convolutional neural network (CNN) to derive an apodization profile that facilitates the design of a narrow, dual-channel filter with identical channels, each featuring a 0.75 nm ...
IEEE29d
MCTGCL: Mixed CNN–Transformer for Mars Hyperspectral Image Classification With Graph Contrastive Learning
To address these challenges, we propose a mixed CNN-transformer network for Mars HSI classification with graph contrastive learning to enhance classification performance. Specifically, we introduce an ...
GitHub23d
Equivariant Neural Functional Networks for Transformers
Tested with conda, python 3.9, CUDA 12.1. conda create -n nfn python=3.9 conda activate nfn pip install -r requirement.txt pip install -e . wget https://huggingface ...
Bloomberg L.P.14d
Recurrent MLP Infrastructure Fund
Connecting decision makers to a dynamic network of information, people and ideas, Bloomberg quickly and accurately delivers business and financial information, news and insight around the world ...
Frontiers25d
Investigation of a transformer-based hybrid artificial neural networks for climate data prediction and analysis
Methods: In light of this, this paper proposes a hybrid deep learning model based on Transformer-Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) to improve the accuracy of climate ...