zuoj's starred repositories
XGBoostLSS
An extension of XGBoost to probabilistic modelling
Zahner-Remote-Python
Examples to control Zahner power potentiostats (PP2x2, EL1002, XPOT2) of the latest generation with Python.
LLMs-from-scratch
Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step
ChineseResearchLaTeX
**科研常用LaTeX模板集
ModelingToolkitCourse
A course on composable system modeling, differential-algebraic equations, acausal modeling, compilers for simulation, and building digital twins of real-world devices
vpncn.github.io
2024**翻墙软件VPN推荐以及科学上网避坑,稳定好用。对比SSR机场、蓝灯、V2ray、老王VPN、VPS搭建梯子等科学上网与翻墙软件,**最新科学上网翻墙梯子VPN下载推荐,访问Chatgpt。
DRL-for-microgrid-energy-management
We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.
Basisformer
This is the pytorch implementation of Basisformer in the Neurips paper: [BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis]
Deep-Reinforcement-Learning-Hands-On-Second-Edition
Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt