Gopal M.'s repositories
QHack2022_PortfolioRebalancing
QHack2022 Open Hackathon Project
Quantum-DSGE
Creating Quantum DSGE method for MacroEconomics
Roadmap-to-QML
This repository will contain the major papers, books and blog posts on QML
approachingalmost
Approaching (Almost) Any Machine Learning Problem
Cryptocurrency-Prediction-with-Artificial-Intelligence
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
forge_public_notebooks
"Pre-executed" notebooks for QC Ware's Forge product
Hackathon2022
CDL Quantum Hackathon 2022
LNN
A `Neural = Symbolic` framework for sound and complete weighted real-value logic
pygrnd
open-source library for simulation, optimization and machine learning
Qillers
Repository for QHack 2022 open Hackathon
qiskit-tutorials
A collection of Jupyter notebooks showing how to use the Qiskit SDK
Quantum-Counselor-for-Portfolio-Investment
The Quantum Counselor for portfolio investment is a tool with two main objectives: forecasting the trend of assets price and optimizing portfolio returns both using quantum computing techniques. For the case of the forecasting method, we use a hybrid method that combines a deep learning model of classical LSTM layers with quantum layers. For the case of portfolio optimization, the quantum algorithms of QAOA and VQE are used to solve the problem and will be compared with CPLEX, a classical solver. Both tools are deeply connected because the forecasted price of the different assets is used for the cost function construction.
quantum-game-theory
Playable quantum game theory games
SelfLearningDistributions
Approximating probability distributions using a QFT sampler. Project for QHack.
SoftServe_QLSTM
We implement a quantum-classical hybrid QLSTM model by incorporating quantum variational layers into the classical LSTM in order to improve the efficiency and trainability of LSTM for better stock price prediction.