@zshicode
github

zshicode

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  • Stars
    star
    399
  • Global Rank 70,030 (Top 3 %)
  • Followers 43
  • Following 17
  • Registered over 7 years ago
  • Most used languages
    Python
         85.7 %
    VHDL     7.1 %
    TeX
         7.1 %
  • Location 🇨🇳 China
  • Country Total Rank 10,894
  • Country Ranking
    VHDL     153
    TeX
         239
    Python
         1,834

Top repositories

1

Attention-CLX-stock-prediction

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction
Python
187
star
2

Deep-Learning-Based-State-Estimation

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm
Python
90
star
3

GNN-for-text-classification

Graph convolutional networks (GCN), graphSAGE and graph attention networks (GAT) for text classification
Python
52
star
4

LaTeX-Beamer-Nankai

LaTeX beamer template of Nankai University
TeX
39
star
5

Raman-Spectra-Deep-Learning

PyTorch implementation of deep learning for Raman spectrum recognition: CNN, LSTM, GNN and contrastive learning
Python
12
star
6

GNN-AttCL-protein

Models and benchmarks for protein classification
Python
9
star
7

Latent-variable-GNN

Combination of latent variable inference and graph neural networks
Python
4
star
8

A-Verilog-VHDL-design-using-python

A basic introduction of Verilog/VHDL design using Myhdl based on Python.
VHDL
2
star
9

Deep-Learning-Raman-Element

Deep learning for element identification using Raman spectrum
Python
1
star
10

GNN-Food-Pairing

Food pairing recommendation based on food-compound matrix and graph neural networks
Python
1
star
11

Deep-Learning-AGV-Control

Deep learning-based Kalman Filter and linear quadratic Gaussian (LQG) optimal control of automated-guided vehicles (AGV)
Python
1
star
12

DL-Food-Taste-QSAR

Deep learning-based food-compound QSAR of food tastes
Python
1
star
13

MambaLithium

MambaLithium: Selective state space model for state-of-charge estimation of lithium-ion batteries
Python
1
star
14

Comprehensive-LP-GNN

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
Python
1
star