xiaoojs20's Stars
PKUFlyingPig/cs-self-learning
计算机自学指南
mlabonne/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
karpathy/nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
rasbt/LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
NLP-LOVE/ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
KindXiaoming/pykan
Kolmogorov Arnold Networks
datawhalechina/self-llm
《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合**宝宝的部署教程
datawhalechina/llm-universe
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
wangshusen/DRL
Deep Reinforcement Learning
linyiLYi/bilibot
A local chatbot fine-tuned by bilibili user comments.
dvgodoy/dl-visuals
Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.
cvxgrp/cvxbook_additional_exercises
Additional exercises and data for EE364a. No solutions; for public consumption.
kebijuelun/Awesome-LLM-Learning
Learning Large Language Model (LLM）(大语言模型学习)
thieu1995/metaheuristics
Implement the-state-of-the-art meta-heuristic algorithms using python (numpy)
km1994/llms_paper
该仓库主要记录 LLMs 算法工程师相关的顶会论文研读笔记（多模态、PEFT、小样本QA问答、RAG、LMMs可解释性、Agents、CoT）
Power-Systems-Optimization-Course/power-systems-optimization
Power systems optimization course materials
warner-benjamin/commented-transformers
Highly commented implementations of Transformers in PyTorch
ShengrenHou/Optimal-Energy-System-Scheduling-Combining-Mixed-Integer-Programming-and-Deep-Reinforcement-Learning
The Source code for paper "Optimal Energy System Scheduling Combining Mixed-Integer Programming and Deep Reinforcement Learning". Safe reinforcement learning, energy management
linfengYang/A-novel-DRO-model-for-self-scheduling-problem
This study is using distributionally robust optimization (DRO) algorithm with conditional value-at-risk (CVaR) to solve self-scheduling problem to obtain a suitable and adjustable self-scheduling strategy
jramak/dual-adp-suc
Code / data for the paper "A Dual Approximate Dynamic Programming Approach for Multi-stage Stochastic Unit Commitment" http://www.optimization-online.org/DB_HTML/2018/06/6672.html
Nan729/RO-and-CC-Emssion-ED
Bridging Chance-constrained and Robust Optimization in an Emission-aware Economic Dispatch with Energy Storage
deep-daya/Grid_Scale_Energy_Storage_Q_Learning
Final Project for AA 228: Decision-Making under Uncertainty Abstract: Grid-scale energy storage systems (ESSs) are capable of participating in multiple grid applications, with the potential for multiple value streams for a single system, termed "value-stacking". This paper introduces a framework for decision making, using reinforcement learning to analyze the financial advantage of value-stacking grid-scale energy storage, as applied to a single residential home with energy storage. A policy is developed via Q-learning to dispatch the energy storage between two grid applications: time-of-use (TOU) bill reduction and energy arbitrage on locational marginal price (LMP). The performance of the dispatch resulting from this learned policy is then compared to several other dispatch cases: a baseline of no dispatch, a naively-determined dispatch, and the optimal dispatches for TOU and LMP separately. The policy obtained via Q-learning successfully led to the lowest cost, demonstrating the financial advantage of value-stacking.
Ecohen4/Energy
R scripts for energy analytics
xb00dx/Online-Courses
Selected Online Courses
AsprinChina/ECM_based_OEF
Data and codes for energy circuit method-based optimal energy flow
ahilbers/bootstrap_uncertainty_quantification
Code for paper "Efficient quantification of the impact of demand and weather uncertainty in power system models" (2020)
akshitgoel48/Distributionally-Robust-Bilevel-Optimization
Pessimistic Distributionally Robust Bilevel Programs
xb00dx/Renewables_Scenario_Gen_GAN
The implementation of scenario generation for renewables production process
christian-cahig/CALOLS
Capstone project for the course EE 257 Optimization in Power Systems.
sriharisundar/MD-RA-USWEST
Code used for the paper "Meteorological Drivers of Resource Adequacy Failures in Current and High Renewable Western U.S. Power Systems"