C++ Rendering Framework w/ MLT, bidi path tracing, etc. and OpenGL Previews (undergrad thesis project from Brown '09)
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Updated
Aug 5, 2012
C++ Rendering Framework w/ MLT, bidi path tracing, etc. and OpenGL Previews (undergrad thesis project from Brown '09)
Simulations Using Markov Chain Monte Carlo Methods
Simulation of random numbers using Metropolis Hastings MCMC technique/algorithm
毕业设计 - Scalable Distributed LDA implementation for Spark & Glint
Implementation of MCMC Algorithms Metropolis-Hastings and Gibbs Sampling
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables
Quasi-Newton particle Metropolis-Hastings
Hierarchical Bayesian approaches for robust inference in ARX models
An implementation of the BUGS example LSAT: item response (http://www.openbugs.net/Examples/Lsat.html) on R. Parameters for the Rasch model are estimated using Maximum Marginal Likelihood as well as Bayesian Inference using jags and an implementation of Metropolis on R.
Metropolis Light Transport (Reading Group)
Probabilistic Models of Human and Machine Intelligence
MCMC Simulation of Hard Disks
Accelerate MCMC algorithm on GPU for Big Data Applications
Virtual population generation, fitting, and benchmarking.
Python development to solve the 0/1 Knapsack Problem using Markov Chain Monte Carlo techniques, dynamic programming and greedy algorithm.
Some methods to sampling data points from a given distribution.
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals
Constructing Metropolis-Hastings proposals using damped BFGS updates
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