Junbo Zhao's Projects
Machine learning of linear differential equations using Gaussian processes
Benchmarks for the Optimal Power Flow Problem
I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
physics-guided neural networks (phygnn)
Physics-informed neural network for solving fluid dynamics problems
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
Solving Optimal Power Flow with Convex Restriction
(Optimal) power flow under uncertainty via polynomial chaos expansion; tutorial example.
CIM interfaces for GridLAB-D and OpenDSS; data and test scripts for the PNNL taxonomy feeders, EPRI large-circuit and DPV test feeders, and some IEEE test feeders.
A Julia/JuMP Package for Unbalanced Power Network Optimization
A Julia Package for Power System State Estimation.
This is an implementation of machine learning methods for power outage prediction. I worked on this project with Ryan, Yanbo and Jerry.
Graph Partitioning Algorithms for Control of AC Transmission Networks
This repository houses the code for the community website http://www.probabilistic-numerics.org
IBR integration simulations
Deep Gaussian Processes in Python
Python Multi-Agent Reinforcement Learning framework
pymgrid is a python library to generate and simulate a large number of microgrids.
PyPSA: Python for Power System Analysis
A library for answering questions using data you cannot see
Matlab code to generate distributed power flow problems.
A list of papers on Generative Adversarial (Neural) Networks