This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market.

[email protected]">

Last update: Dec 25, 2022

Overview

GPlearn_finiance_stock_futures_extension

This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market. More specifically, this is an implementation that uses the GPlearn's symbolic transformer to find the alpha factors of the PTA futures contract listed in the Zhengzhou Commodity exchange located in China. Although this implementation has successfully found some alpha factors that have some ability to predict, there is always risk involved in any kind of financial trading.

The definiation and related resources surrounding GPlearn and alpha factors are also included in the notebook.

Be cautious while trading.
Be cautious while trading.
Be cautious while trading.
Be cautious while trading.

Owner

Chengwei [email protected]

I have just finished my economic studies undergraduate degree at UCSC and applying for master's degree.

[email protected]">

GitHub Repository

python debugger and anti-vm that checks if you're in a virtual machine or if someones trying to debug your file

Anti-Debug was made by Love ❌ code ✅ 🎉 ・What it checks for ・ Kills tools that can be used to debug your file ・ Exits if ran in vm (supports different

31 Aug 09, 2022

Baseline powergrid model for NY

Baseline-powergrid-model-for-NY Table of Contents About The Project Built With Usage License Contact Acknowledgements About The Project As the urgency

6 Nov 24, 2022

This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"

Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater

0 Jan 05, 2022

Modeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis

Modeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis This is a PyTorch implementation of the model described in our pape

6 Jul 08, 2021

Predicting Event Memorability from Contextual Visual Semantics

0 Oct 06, 2021

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte

201 Nov 09, 2022

Public implementation of "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression" from CoRL'21

Self-Supervised Reward Regression (SSRR) Codebase for CoRL 2021 paper "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression "

19 Dec 12, 2022

An OpenAI-Gym Package for Training and Testing Reinforcement Learning algorithms with OpenSim Models

Authors: Utkarsh A. Mishra and Dr. Dimitar Stanev Advisors: Dr. Dimitar Stanev and Prof. Auke Ijspeert, Biorobotics Laboratory (BioRob), EPFL Video Pl

16 Dec 13, 2022

Powerful and efficient Computer Vision Annotation Tool (CVAT)

Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our

8.6k Jan 01, 2023

Code for "Multi-Compound Transformer for Accurate Biomedical Image Segmentation"

News The code of MCTrans has been released. if you are interested in contributing to the standardization of the medical image analysis community, plea

97 Jan 05, 2023

Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021)

Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021) Tensorflow implementation of Bridging the Gap between Label- and Reference-ba

8 Jul 13, 2022

Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU

1.2k Dec 29, 2022

Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

330 Jan 07, 2023

Visualizer for neural network, deep learning, and machine learning models

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens

21k Jan 06, 2023

A Closer Look at Structured Pruning for Neural Network Compression

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

140 Dec 05, 2022

🚀 An end-to-end ML applications using PyTorch, W&B, FastAPI, Docker, Streamlit and Heroku

82 Jun 26, 2022

A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution

DRSAN A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution Karam Park, Jae Woong Soh, and Nam Ik Cho Environments U

4 May 10, 2022

This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).

The Neural Process Family This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CN

892 Dec 28, 2022

Supervised Classification from Text (P)

MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from

1 Nov 22, 2021

MAVE: : A Product Dataset for Multi-source Attribute Value Extraction

The dataset contains 3 million attribute-value annotations across 1257 unique categories on 2.2 million cleaned Amazon product profiles. It is a large, multi-sourced, diverse dataset for product attr

89 Jan 08, 2023