Pinned Repositories
circuit_training
lazer
just for study
mapmatcher
A simple map matching library using the Hidden-Markov Model Map Matching algorithm (HMM Map Matching) from Paul Newson and John Krumm, "Hidden Markov Map Matching Through Noise and Sparseness", 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2009), November 4-6, Seattle, WA, pp. 336-343. It is designed to be used from R and uses the GeOxygene implementation of the algorithm.
MapMatching
Bachelor Graduation Project, designing a faster real-time map matching algorithm based on MSRA paper
Optimal-Edge-Server-Placement-using-K-means-and-PSO
Optimal placement of edge servers using K-means Clustering and Power allocation using Particle Swarm Optimization
paac
Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning
PlacementEssentialReadings
stan
Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
stanVI
VI on trust region
wxjzte's Repositories
wxjzte/circuit_training
wxjzte/Optimal-Edge-Server-Placement-using-K-means-and-PSO
Optimal placement of edge servers using K-means Clustering and Power allocation using Particle Swarm Optimization
wxjzte/PlacementEssentialReadings
wxjzte/MapMatching
Bachelor Graduation Project, designing a faster real-time map matching algorithm based on MSRA paper
wxjzte/stanVI
VI on trust region
wxjzte/lazer
just for study
wxjzte/stan
Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
wxjzte/paac
Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning
wxjzte/mapmatcher
A simple map matching library using the Hidden-Markov Model Map Matching algorithm (HMM Map Matching) from Paul Newson and John Krumm, "Hidden Markov Map Matching Through Noise and Sparseness", 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2009), November 4-6, Seattle, WA, pp. 336-343. It is designed to be used from R and uses the GeOxygene implementation of the algorithm.