四川大学非官方Beamer模板 | Unofficial Beamer Template for Sichuan University

国家自然科学基金申请书正文（面上项目）LaTeX 模板（非官方）

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

A recursive framework to enhance the efficiency of deep unfolding networks.

Beamer template based on Flux-beamer

TeraMIMO: A channel simulator for wideband ultra-massive MIMO terahertz communications.

These codes simulate the following paper: Simon Tarboush, Anum Ali, Tareq Y. Al-Naffouri, "Compressive Estimation of Near Field Channels for Ultra Massive-MIMO Wideband THz Systems", ICASSP 2023 - …

Pytorch codes for "An Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation" in IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2023.

RIS-Codes-Collection: A Complete Collection Contains the Codes for RIS(IRS) Papers.

Implement reinforcement learning(RL) based on parameterized quantum circuits with quantum computing cloud Quafu.

Implementation of deep reinforcement learning algorithms for training an agent to play the game lunar lander

LaTeX package and annotated examples for annotating equations using TikZ.

This code is written in MATLAB to Evaluate the I function (Generalized Fox F-function)

Data Analysis with Python

Contains notebooks solved as part of the course Quantum Machine Learning

TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning 🔥 ⚡ 🌈

Learn Quantum Machine Learning using pennylane framework

A curated list of papers, blogs, and research publications in the field of Quantum Machine Learning

Quantum-classical hybrid convolutional neural network for classical image classification

This is the code for the paper "Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMO"

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Code for implementing and experimenting with quantum algorithms

The current notebook implements a simple disaggregator for deep-nilmtk models compatible with NILMtk.