Stars
Repository containing most of the source code (LaTeX, Python, etc.) of all experiments and papers I have been involved with.
A pytorch implementation of "SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data"
Unofficial Pytorch implementation of SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pretraining https://arxiv.org/abs/2106.01342
A PyTorch Lightning-based library for self- and semi-supervised learning on tabular data.
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
An open source python library for non-linear piecewise symbolic regression based on Genetic Programming
A PyTorch implementation of DeepFM for CTR prediction problem.
This method is a new oversampling algorithm and can circumvent the deficiency of WK-SMOTE (and SMOTE as well as its variants) caused by randomly selecting some minority class samples.
A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, anomaly detec…
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
Image Generator for Tabular Data (IGTD): Converting Tabular Data to Images for Deep Learning Using Convolutional Neural Networks
High-Performance Symbolic Regression in Python and Julia
DANets (a family of neural networks) for tabular data classification/ regression.
Code for paper: NCART: Neural Classification and Regression Tree for Tabular Data
Implementation of SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption in Pytorch, a model learning a representation of tabular data using contrastive learning. It is inspire…
This project processes financial data for predictive modeling, covering data concatenation, sampling, division, and train-test split. It explores feature selection methods like LightGBM, Lasso, and…
Detecting Fraudulent Blockchain Accounts on Ethereum with Supervised Machine Learning
Model stacking example on toy dataset using XGBoost, LightGBM and more, combined with mlxtend model stacking.
predicting student academic performance
deep learning for image processing including classification and object-detection etc.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image