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Approximate Multiparametric Mixed-integer Convex Programming
Software Platform for solving and manipulating multiparametric programs in Python
Source code for the paper titled: "Unlocking the full potential of smart charging: Addressing paused and delayed charging problems in electric vehicles", accepted to be published in Nature Communic…
Regulation strategies for electric vehicle-grid interaction
Data and codes for my paper Co-Optimizing Bidding and Power Allocation of an EV Aggregator Providing Real-Time Frequency Regulation Service
Source code of our paper "Solving Constrained Variational Inequalities via a First-order Interior Point-based Method", ICLR 2023.
Computing confidence intervals for stochastic variational inequalities and stochastic optimization problems.
Minimax Optimization, Monotone Variational Inequalities
A parameterisation and optimisation package for battery models.
A collection of Benchmark functions for numerical optimization problems
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
Performance Robustness Evaluation for Statistical Classifiers
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure
Awesome Machine Unlearning (A Survey of Machine Unlearning)
A data structure for mathematical optimization problems
OptNet: Differentiable Optimization as a Layer in Neural Networks
整理开源的中文大语言模型,以规模较小、可私有化部署、训练成本较低的模型为主,包括底座模型,垂直领域微调及应用,数据集与教程等。
DRL-based ESSs scheduling environments in distribution networks.
A one-stop data processing system to make data higher-quality, juicier, and more digestible for (multimodal) LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大模型提供更高质量、更丰富、更易”消化“的数据!
Simulation and Computing Toolkit for Power System with High Penetration of Renewable Energy Sources
Conformer-RLpatching achieves multi-objective dispatching for the hybrid power system under the long-term fluctuations of renewable energy
CS198-96: Intro to Neurotechnology @ UC Berkeley
OpenEnergyPlatform / awesome-sustainable-technology
Forked from protontypes/open-sustainable-technologyOpen development environments to preserve global energy supply and vital natural resources
Experiments for distributed optimization algorithms
Focus to integrating probabilistic constraints to manage uncertainty in portfolio optimization is an innovative approach that addresses the limitations of traditional deterministic models.
Stochastic Optimization under Uncertainty in Python.
This is the code provided to support the paper of "Stackelberg Game Theory Based Optimization Model for the Design of Payment Mechanism in Performance-Based PPPs"